interactive design research band 2 of bhubaneswar agro...
TRANSCRIPT
Need Assessment Survey Report
Interactive Design Research—Band 2
Of
Bhubaneswar Agro Processing Cluster
Sponsored by
“Design Clinic Scheme, Ministry of MSME, Govt. Of India”
Under an Agreement with National Institute of Design, Ahmedabad, the Implementing
Agency, and Central Toolroom and Training Centre, Bhubaneswar
Prepared by
Dr. N. P. Gantayet, (PhD) and Prof. S. K. Nanda (Retd Prof OUAT)
November 2013
120, Madhusudanagar, Bhubanesar-751001, Phone 06742390311, mob: 09937631559
www.thermo_orissa.com; e-mail: [email protected], [email protected], [email protected]
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ACKNOWLEDGEMENTS First of all the author wishes to thank the individual entrepreneurs of Farm Enterprises units for
their excellent cooperation, patience, and enduring the questions put to them.
We owe special thanks to Mr. Swaraj Mahanti, who organised most of the visits and took us
round to meet key officials in Ranpur and Bhubanesar, Thanks are due to him for organising the
meetings with farmers, Agri entrepreneurs, and SH Cooperatives in that area.
Dr. Mahendra Mohanty, Associate Professor, CAET OUAT has provided valuable inputs in Food
Processing. Dr. P. L. Pradhan, Associate Professor, deserves special mention for making much
of the material for cluster level analysis, and sharing his experience with farmers. Prof Mohd
Khalid Khan and Prof. Debaraj Behera have provided the latest Research trends in Agro
Processing and Farm Machinery from their work and lecture notes.
We express our thanks to co-designer Er Pragati Rout. Shri Saroj Jena and Shri Jyoti Behera
deserve special mention for providing assistance in graphics and drawing.
Mr. Ambuj Nayak, Head Marketing, CTTC has not only accompanied in the visits, but has gone
out of the way to help and see that the NAS went on smoothly. Shri S S Dhada, Asst, Director,
PIB, has given many valuable inputs in Communication. He is not only a friend, but a patient
teacher as well about usefulness of media in Agriculture. My special thanks for getting material
translated into Odiya and getting the Press Release that has made the NAS a mite easier.
Thanks are due to Mr. Ashok Mondal from NID, Co-ordinator, East Zone, DCS, and Prof
Sashank Mehta, Head DCS programme from NID provided guidance and patience throughout
the survey. Thanks are due to also Shri Sibasis Maiti, GM CTTC, for not only his advice and
experience, but facilitating the smooth conduct of the NAS, and the imminent workshop. Funds
from the Dept of MSME for the grant portion are gratefully acknowledged. Lastly, thanks are due
to officials who were visited and have extended support and inputs for deeper understanding of
the cluster in the Region.
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LIST OF PARTICIPANTS IN THE NAS
Sl No Name Products (Agriculture Produce and Services)
Contact Address
1 Sri. Swaraj Mahanti Horticulture, Custom Hiring Services
Ranpur, Nayagarh, Mob 9937340776
2 Sri. Manoranjan Singh Custom Hiring Services Village Beraboi, Delanga, Puri, (Mob: 9937280609)
3 Sri Samarendra Singh Custom Hiring Services Kusupur, Gop, Puri (Mob: 889596166)
4 Sri Bipin Khatei Paddy, Custom Hiring Services Bindha, Pippili, Puri (Mob: 9437178626)
5 Sri Dhussan Rout Paddy, Custom hiring Services Kakudikosanga, Pipiili, Puri
6 Sri Kishore Rout Custom Hiring Services Auduspur, Jajpur
7 Sri Arun Kumar Panda Custom Hiring Services Kalamatia, Bari, Jajpur (Mob: 9658570193)
8 Sri Pabitra Baral Custom Hiring Services Nauagaon, Dhenkanal
9 Sri Bhibu Mohapatra Custom Hiring Services, Contract Farming
M/s Bioworld
Satya Nagar, Bhubaneswar
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INTRODUCTION “The most happening event in Union Budget 2013 was that it was a non event.” This is how an
analyst described the Union Budget. Four events were given to justify calling the Budget a non-
event: (1) The current UPA government did not have any source of funds to finance the
promises (sops) given to electorate, and the money had to be thinly spread, (2) government was
leaning to the left leaving the centre fold (manufacturing-the wealth generator?) to others, (3)
money from budget heads of the previous year were taken out to finance Budget commitments,
(4) the budget did not matter. The happening event was the last illusion of a government, not
sure of its chances, to hold onto power at all costs. (TOI, Mar 01, 2013, Union Budget Special)
Only the last has some truth in it. It is a timeless truth; which government would not do anything
(legally) to stay in power? In the event, the one thing that overturned the analysis on its head
was Murphy’s Law; “if anything has to go wrong, it will go wrong”. An external threat turned the
misreading of the past into a prophecy for the future.
Dollars took flight, causing manufacturing to slump (as against reason no 3 of the UPA
government deserting production by withdrawing money from previous commitments).
The Rupee’s purchasing power fell due to widening Current Account Deficit, inflation
shooting up, and Consumer Price Index touching the roof, (as against reason no 1 of
spreading the budget very thin to finance election sops).
Government leaned to the left with Food Security Act, because Agriculture was the only
sector left after manufacturing failed to deliver growth, jobs, and security due to falling
export demand (as against reason no 2 of leaving the centre fold to someone else).
RBI Governor Raghuram Rajan increased liquidity, offered to swap dollar deposits, took
steps to increase rural credit, adjusted cost of the Rupee upwards in internal borrowings,
and enabled Rupee investment in Agriculture supply chains. Government allowed 100%
FDI in Retail (as against reason no 4 that the Budget did not matter.)
Given the facts, ceteris paribus, prediction of analyst was reasonable. These events happened.
What upset his reasoning was Future Shock. The future came up suddenly, and not in the
expected sequence. (Notice the change in order of events as it unfolded against prediction).
This underlines the advantages of Design Thinking against Analytics Thinking. Synthesis is the
task of Design Thinking. Design lives only in the present, and thus achieves timelessness.
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As Wittgenstein said, “If we take eternity to mean not infinite temporal duration but
timelessness, then eternal life belongs to those who live in the present.” This is true for Design
Thinking as well as for Agriculture, whose timelessness goes back beyond remembered history,
and would outlive the rise and fall of many civilisations yet to come. The analyst needed only to
have looked into the events of the present to overcome Future Shock, by unlearning and
relearning. If the TOI Press clipping (given below) has to be believed, the Govt. of Odisha was
unlearning its recent past and relearning to live in the present.
A DAP seminar on Agro Equipment cluster on Feb 22nd, 2013, independently highlighted these
same issues as in the averments made in TOI in the Press Clipping given above. This event
was followed by the Union Budget-2013 on Feb 28th, 2013. The Union Govt. was preparing a
significant agenda for GDP growth, and put all its eggs into Skill Development basket as the
vehicle for jobs, GDP growth, economics, and winning elections 2014. Union Budget was also
preparing the ground for a long overdue Agriculture Reforms to look upon it as a market rather
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than as a production activity. A market is an efficient system for distribution of entitlements if it
has norms. It was a major shift in paradigm, to keep a “people centric” approach and come out
of the feudal caste based system that was unable to provide economic and social security.
The seminar highlighted key issues that faced Agriculture market.
With more than 60% people dependent on Agriculture, the major challenge is distribution
of the wealth created, whether from the surplus from Agriculture or mining
MSME have a role to play in the equitable distribution of surplus and Resource allocation
Farming had become women labour intensive, creating a new set of issues in Resource
allocation. Approaches had to be Gender Sensitive, bottom up.
Labour cost had gone up, and were not available in the numbers required; women would
not travel more than 2 kms from their homes in search of work even if they forego wages
60% of farmers belonged to SMF category, 1-2.5 Ha. More than 90% of farming was
powered by animal energy and human labour.
This DAP of Band 2 was tied with a DAP (Band 5) of the Agriculture Equipment cluster. Apart
from the fact that both the clusters had participated in the seminar and found common ground,
there are other reasons why a tied DAP (NAS and Workshop) was considered as necessary.
Systematic Agriculture is associated with tools, and is a mark of civilisation’s progress.
The other theatre of civilisation’s progress where tools developed was in fighting wars.
Equipment manufacturers and users were decoupled due to a variety of reasons, which
could be addressed only by a joint effort and finding common meaning
The Odisha Agricultural policy unveiled three months after the DAP seminar, but before
this NAS, was committed to market (enterprise) approach after the Food Security Act.
It had, in fact, gone one step ahead by selling rice at Rs 1 per kilo at the cost of state
exchequer with the message of increasing “worker” productivity
This NAS report for Agro Processing cluster is a sequel to the NAS report of Agriculture
Equipment cluster. The NAS would use the same premises of Design Thinking as the previous
report. This would assure that voices on both sides of the divide are heard by either.
Methodologies used are given briefly, and the reader is referred to the other report for details.
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OBJECTIVE AND ACHIEVEMENTS OF NAS For the cluster, the DCS programme offers an opportunity to become corporate. Cluster players
in the NAS list are all erstwhile farmers, who have also developed Custom Hiring Services to
outsource spare capacity. Agro Processing/Food Processing is an emerging field in the state,
started recently by Odisha Food Processing Policy 2013 that is linked to Odisha Agriculture
Policy 2013. The cluster knows about business, but awareness about corporate functioning is
rather poor. Farming as an occupation has its own hazards. The vagaries of Nature, the
uncertainty of markets, and changing priorities of politicians, can be very daunting. When
compounded with risks of business, these factors can deter anyone from going corporate.
The overall objective of the DAP was adopted as follows:
Objective: To become a body corporate of appropriate design for maximising individual growth
from opportunities thrown up by the enabling environment Agriculture/Food Policy
The objective aligns very well with Agriculture Policy and Food Processing Policy that views the
sector as a market. But it would take time to seep into the target group (farmers) to call
themselves as entrepreneurs and farming as an enterprise. Policy makers are aware of this,
and hope to bring about change through intense extension activities. The Policy envisages that
the linkages would function better than a departmental approach, especially by involving private
enterprise. Enticements include PPP, and of course, liberal execution drivers for growth of
MSME in the sector such as investment subsidy, lower interest, Skill Training, diverse methods
of information sharing, credit availability, market assistance, social security of workers, etc.
Achievements 1. Awareness to make appropriate choices in technology and investment by making best
use of Design Thinking and use of Natural Resources
2. Awareness about importance of Skill Development process as an effective enabler in
taking up Remedial Designs and New Product Introduction
3. The importance of extended Enterprise Social Responsibility by forming a cluster for
dissemination of best practises and adoption of new techniques/methodologies
4. To make Value Added goods for improving viability of composite farming and processing
5. Change in behaviour to keep with esprit of Policy towards a demand based approach
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CLUSTER HISTORY AND PRESENT SCENARIO The cluster has just started to form and is in nascent stage. The DAP seminar on Feb 22nd 2013
was the first bold attempt to identify it as a cluster within meaning of the definition of Cluster
Development Approach of DC-MSME, GOI. This was to bring the benefits of the Cluster
Approach to the region. There had been an earlier effort by Govt of Odisha to encourage
formation of Agri Enterprises by creating APICOL, and creating Custom Hiring Centres under
the aegis of the Govt. Such efforts got the Ganjam, Rayagada, Koraput, and Bargarh Rice Mill
clusters into the first list prepared by UNIDO in 2000, and Spice Cluster in several other districts
like Cuttack, Kandhamal, in subsequent lists.
The DCS programme (DAP Seminar) had been used earlier (2011) to identify Khadi cluster,
which incidentally carried the Food Processing burden, inter alia, KVIB and PMERY. According
to figures given in Food Processing Policy 2013, there were 24,811 enterprises (mostly under
SH Cooperative Act + EM1 under MSMED Act) with employment of 1.3 lakh and investment of
Rs 1,519 crores. Investment would jump many fold by policy incentives to encourage growth
through MSME (EM2). Projects already cleared stood at Rs 1,335 crores. Resources to this
sector (feedstock) would come from Agriculture products grown in the state, including food grain
production (around 86 lakh tonnes), livestock, dairy products, fisheries, and Forest Resources.
So this cluster around Bhubaneswar and other clusters belong to unorganised sector and have
just started writing their history. But the roots go deep, and its progenitors are as old as the
beginning of civilisation marked by use of tools in Agriculture.
A brief History of Agriculture in Odisha would be too long to write about. The State Agriculture
Policy 2013 is the best view one can get of the history of Agriculture, as it endorses and enables
practises that has evolved through generations. It has a Postmodernism view of Agriculture. It
cannot be otherwise. An average land holding of 1.25 lakh Ha, 93% of it powered by Animal and
Human energy, mostly rain fed irrigation, and an inadequate distribution system, shows that
modernity would have uncontrollable downside effects. A “people centric” approach by building
on previous efforts of governance systems like Watershed (since 2000), and society building
(social engineering) by increasing “organisation” density is not only necessary, but should be
mandated in any Policy for this sector.
Design Thinking can be used as Occam’s razor to cut out histories of the cluster that are not
relevant to Design Point of view. This is easily done by using Design Thinking to analyse only
those portions of the Agriculture/Food Policy applicable to MSME Units under focus in this NAS.
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METHODOLOGY From a Design Point of View, Policies are looked upon as “degree of freedom” for maximising
certain variables such as growth, ROI, revenue, wages, market share, etc. using Design
Thinking as an objective function. It is similar to being given an outline of a story, and being
asked to develop a plot and write a script for dramatic impact with a view to generate
commercial value. The methodological issue for Food Processing Policy analysis in the “eyes”
of Design Thinking is to remain within mainstream economic thought that underlies the Policy. A
collateral objective was to also satisfy the DAP MSME participant’s objective given on page 6.
Mainstream economic thinking as maybe known from the events of the last three months
appears to be “rural wages would drive wealth creation (capitalisation)”. The government is wary
that the QE stimulus package of the US would taper off, and one should be prepared for it. If
there were some way rural wages could be stimulated from Agriculture, the economy would
bounce back. Obviously, wages would not go up without investment and production. A slew of
measures followed, such as the various Acts, Policies, Interest Rate hikes, and Banking
Administration. In economics, it is the net aggregate income from wages that matters, since that
would also increase expenditure and demand for goods. As explained by analysts writing in
newspapers, the surplus of income over expenditure in Agriculture markets would create
demand for goods manufactured by industry. (A sustained expenditure needs surplus.)
A MSME would analyse Agriculture/Food Processing Policies of State Govt. of Odisha to search
for feasible opportunities in light of mainstream economic thinking. The approaches towards
determining the feasible set of actions in an emerging market is given as follows:
The first is capability; meaning that the emerging technology should be a blend of two or
more old technologies over which the MSME and the rural worker have good mastery.
The second is what control strategy is used to overcome variations in costs, whether it is
a feedback control or a feed forward control system.
In both of these determinants of feasibility, Design Thinking would be of good use. In the context
of Design, Policy measures to maximise productivity create opportunities for Skill Building.
To assess capability, it is important to know the historical evolution of the cluster. A Policy
document is an excellent source of cluster’s history and capabilities, since it makes Resources
and incentives available for extant capabilities. In Agriculture/Food Processing, an esoteric
Technology recommended by Policy would be considered as madness. As a Policy is for all, the
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document contains more information than what is necessary for a MSME’s product. A MSME
making meat products has no use for provisions for horticulture preservation. In such cases
Design Thinking functions like Occam’s razor to cut away all that is not necessary for the
product’s Design, and reduces the number of variables to a manageable few.
The role of Design Thinking in control strategy is a bit more complicated. Assuming the first
hurdle is crossed, the control of the output variable, say cost, can be a feedback control system
or a feed forward control system. A feedback control system would mean where corrective
action (remedial) is taken to manipulate inputs based on the observed deviation of the output
cost from the set point, such as price that has been bargained or quoted to customer. The role
of Design Thinking is to change the blending of inputs so that the blended cost matches the
desired output cost. A feed forward control system would mean that the cost is blended on the
assumption that it would match the output cost. Generally, a feedback system gives better
control over the cost, whereas a feed forward control has inherent instability.
Examination of Odisha State Agriculture/Food Processing Policy shows that from the
perspective of the MSME, it uses feed forward control mechanism to follow the Central Policy of
raising aggregate rural wages. Policy provides incentives to create Mega Food Parks that would
comprise of a collection of MSMEs, and all rural supply chains from production and collection
centres would converge to these “hubs”. From these “hubs”, products would be distributed, and
some of them would be exported.
Feedback Mechanism: The existing “hubs” (Cuttack, Berhampur, Sambalpur) have formed
over past so many years as mandis for marketing the raw Agriculture Products, such as
vegetables, food grains, pulses, oil, etc. There is an exchange of goods between rural centres
and mandi cities, such as equipment and other manufactured goods that are used in production.
This is the feedback mechanism that is used for blending of costs. The Agriculture Policy has
provisions for strengthening these Terminal Centres, formed and shaped by history and culture.
Feed forward mechanism: Mega Food Parks are envisaged being equipped with the latest
technology to produce the “blended cost”, as it has proved effectiveness for doing it in other eco
systems. Some products would be exported, and sent to other states through the connectivity of
the Food Security system (not yet operational). The demand created for Agro products would
raise wages as rural production increases to meet extra demand (the feed forward mechanism).
What these Mega Food Parks would give in exchange to the rural centres is not clear, and is
probably not known; as such reciprocal transactions have no support of history and culture.
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Small spikes in the supply chain, such as temporary suspension of supplies due to natural
causes, can send cost spiralling out of control in feed forward control strategies. Fire fighting
done by dousing the fire is generally not considered as good strategy. One needs to correct
structural defects, such as removing inflammable material where it could spread, or cutting off
further supply of inflammable material, while at the same time dousing the fire. Feedback control
strategy needs knowledge of Design Thinking to reveal possible structural defects in MSME or
in Policy, so that the MSME is safeguarded against risks.
Lesson in Design Thinking from RBI Governor Raghuram Rajan: Contrary to popular perception, Futures, Swaps and Options use the Feedback Control strategy for controlling cost. Soon after assuming office, RBI Governor Rajan opened a window for swapping dollar deposits for a period of three years. The next action was to make the cost of funds after blending with swap window funds same as the prevailing cost of funds. Some Banks (including SBI) showed reluctance, since the blended cost of funds in India was cheaper than the blended cost after mixing the funds obtained from the swap window. Subsequently, Rajan increased repo rates (interest rates of funds borrowed by Banks from RBI), and slashed rates of short term funds, with other measures to improve liquidity and improve circulation in rural areas. These measures made the cost of funds from the two blended funds equal. The result, the dollar funds collected from the swap window came to 1.2 billion dollars in 3 months.
A similar method is followed in Design Thinking, which manipulates blended cost by varying (a) technology, (b) Skill Sets, (c) procedures in workstations, keeping the cost to customer the same. Note the aggregate cost of funds flow in a time period have to be assessed (area under the curve, or investment) and fixed rather than the exchange value of funds, which is a rate like interest rate or ROI. In Design Thinking, aggregate functionality over lifecycle is used as feedback to control within performance specifications like throughput, power, etc.
In this report we sometimes use the term cost function instead of cost, and the term investment
or returns for aggregate cost. A time period would mean the PLC (Product Life Cycle) period. A
PLC period comprises of many Budget periods, 5 to 7 years or more.
Product (feature) Design is a variable in Design Thinking, as customers generally want cost to
be fixed. Equipment sellers (Technology Providers) very often use swaps, i.e. manipulate
feature designs with higher Unit Cost so that the customer’s blended aggregate cost comes
down; viz. cumulative investment (expenditure) in material, labour, energy, maintenance, etc. for
the PLC period comes down. The customer in turn would alter its workstations and product
feature design for its clients in the PLC period of the product it manufactures. When Design is a
strategy in marketing, PLC periods of feature designs are blended as per client’s need. The
operations of blending costs in the workstation constitute the core of Design Thinking.
Workstations spanning across MSME Units in Agro/Food Processing is given in Figure 1.
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Figure 1: Cloud of Points Covering Workstations of Agriculture Sector
100 oC, P: 80 mm H2
Refrigeration Plant
UNIT OPERATIONS Of
FOOD PROCESSING
Proposed Retrofit
Food Products
Bagasse (Waste) FC=25%
Bioreactor
Algae
Sunlight
Power Plant (Fossil Fuel)
SOLVENT
UNIT OPERATIONS OF
AGRO PROCESSING
Air
Flue Gas
Air
Chimney
Packaging
Food Market
Electricity (Grid Supply)
Carbon Credit Market Greenhouse Gases
Biodiesel Production
DIARY CLUSTER
600oC
Co-Generation Gasifier Technology
Heat Loss
Heat Loss
Heat Loss
Heat Loss
Biofuel Market
Proposed Substitution
Cracked Fuel (Hydrocarbons)
Flue Gas
Steam Generation)
AGRICULTURE AND SPICE, CLUSTER
AGR
O P
RO
CES
SIN
G C
LUST
ER
FOOD CLUSTER
BIO
TEC
HN
OLO
GY
CLU
STER
Biogas
BIO
DEI
SEL
CLU
STER
Dire
ctio
n of
Incr
easi
ng V
alue
Add
ition
and
Ent
ropy
Direction of Increasing Entropy
COTTON CLUSTER
Sunlight
Up Land
Low Land
Coal Mining
Cattle Feed Market
Solar Power
Cotton Ginning
Khadi Spinning
Yarn Finishing
Weaving
Apparel Making
Textile Market
KHAD
I C
LUST
ER
Unit Operations of Agriculture-Low Land
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“Workstation” to Store Ginger
Storage of Organic Mass is an active workstation, since there are significant expenses involved in Unit Operations for creating correct ambient conditions for preservation, such as refrigeration, addition of fungicide, air tight packaging, leaching, preservative, dehydration, and so on.
WORKSTATION AND MACHINE TOOLING Figure 1 is a graphic representation of the Odisha Agriculture/Food Processing Policy 2013.
Markets are coloured in blue boxes. A “market” would mean “one of the many varieties of
systems, institutions, procedures, social relations and infrastructures whereby parties engage in
exchange for barter or money”. The flowchart can be looked upon as Capital Flows within and in
between markets of Agriculture/Food Processing. As an institution, markets would mean many
suppliers and many buyers, where price settlements are mediated by third party arbitration, like
courts, policies, law, administration, and other instruments of the state.
Workstations would be represented as points in the flowchart in the neighbourhood of which
activities take place. The yellow coloured boxes are Operations under review in the NAS. In this
flowchart, the workstation is a place for one or more Operations. A Unit Operation in Agriculture,
Agro Processing and Food Processing describes a particular type of function such as cutting,
shelling, grinding, mixing and blending,
extraction, distillation, and so on. A workstation
in a Capital flow-chart is a Cost Blender that
mixes Skill Sets, technologies, and procedures,
and processes input material from upstream
workstations, and gives outputs that are sent to
downstream workstations. In the flowchart (of
Capital Flow), cost is a (density) function of the
variables of the workstation, usually given by
units describing flux, or rate, such as interest
rate, rate of return, income on daily/hourly basis,
and depreciation.
A volume (aggregate cost or cost) used by
Accountants is the area under the curve, or
integration using definite integrals in a time
interval. In a cost function chart (graph), the workstation is a point with infinite curvature, where
the cost function (e.g. rate of return) encounters an asymptote. For example, paying more to a
worker skilled only in farm work would not yield processed and cleaned agro products. Different
Skill Sets have different rates. Asymptotes are points of discontinuity, a Black Hole where funds
would simply get swallowed up, and more addition of cost would yield only negligible returns.
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Unit Operations of Agriculture sector can be divided into three types depending on functionality
1. Unit Operations of Agriculture, i.e. operations from primary tillage to harvesting
2. Unit Operations of Agro Processing or Post Harvesting Operations, from threshing to
food processing unit, including storage and preservation
3. Unit Operations of Food Processing, from raw product to dining table
The Design Parameter for characterising all Unit Operations is energy.
Design Parameter for Fabrication: In fabrication (structural fabrication,
machining, and casting) weight used as Design Parameter correlates well with
fabrication costs. Difference in product cost that may have the same processing
cost is due to materials. The correlation coefficient is modified according to
material and shape complexity of the part. An example with shape complexity
differences would be between a cylinder and a cam or connecting rod. For
example, cost of casting cast iron, steel, and stainless steel is same if process is
same, say induction melting and casting, but stainless steel is around ten to sixty
times costlier than Cast Iron. Process would normally change with material, such
as in casting when a more volatile alloying metal like Titanium is used.
Unit Operations of Agro (Post Harvest) Processing The correlation coefficient between energy and throughput is modified by (a) type of Unit
Operation, (b) single or multi functional,
(c) characteristics of bio material (that
influences process)
These Unit Operations account for
significant amount of energy in the Flow
Chart given in Figure 1. Most of it is
untapped due to wrong planning of the
upstream Unit Operations of Agriculture
as shown in the photograph. For every 1
kg of food product by weight, the
biomass generated is around 9.5 kg.
The wasteful burning of residual
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Happy Seeder
Threshers in Open Field
Par Boiling (Small
Scale)
biomass after harvesting results in methane addition
in the atmosphere, nutrient and biomass addition to
soil is not done. One way for tackling the problem
was seeding with the biomass still intact, as shown
in the photograph.
This is a partial solution, however, and the best that
can be done is to collect the biomass, which
necessitates improvements in equipment redesign
for collection, and technology to use lean fuel. For
example, the Power Tiller / Tractor thresher
generates fine dust and solids that are a fine source of fuel for different purposes, such as par
boiling, drying, or even cooking. It has
been demonstrably shown that a
village of around 60 households can
get sustained power for around six
hours per day, 365 days of the year,
which is sufficient to light households
in the night for studies of
schoolchildren and TV, operate all the
LI pumps, a rice mill and other post
harvesting operations, and also other
sundry activities like running a
compressor for filling in air of tyres.
The innovation needed is in pricing,
and deciding the right technology mix,
(all old technologies). This is to say
that the innovation is in Social Engineering, by integrating technologies panning across
workstations of Figure 1.
Two steps taken in this direction by the Policy are: (1) to treat the Agriculture sector as a market
(inter connected markets) rather than as a Growth Pole dependent on one “hub” for everything,
and (2) converting farmers and farmer clusters to enterprises (corporate) from their current
status as a Self Help Cooperative to the MSMED Act. The NAS shows that a third role for the
sector would be to make them as energy managers of agriculture with pecuniary benefit.
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Chaff Cutter
Emerging Opportunity for Food Processing: The process of a rational energy security begins with preparation of fuel. The innovation consists of achieving zero carbon footprint for this Unit Operation, (a) collect dust (loss prevention), (b) producing more than required feedstock for cattle, (c) meeting energy requirements for domestic requirements. The technology mix required is (a) cookstove, (b) partial gasification, (c) CO2 sequestration, (d) ash used for non critical construction, and (d) lean gas combustion
Unit Operations of Food Processing Food Processing being in the nascent stage, none in the NAS sample have taken it up as an
industry. The Odisha Food Processing Policy 2013 based on the experience of pilot projects of
the NMFP (National Mission for Food Processing 2012) is yet to “explain” to general public
(farmers) the benefits of its adoption on a wide scale, across scales.
An estimated 35-40% of primary food
produced goes waste due to lack of
storage and conversion to a state where
it can be preserved, such as dehydration.
Using energy as a Design Parameter, the
direction for waste reduction appears to
be a decentralised utilities with priority on
meeting energy needs for certain basic
social needs. The latter is to make it
profitable when taken up by an enterprise,
as slogans of energy thrift and
conservation does not appear to get
reflected in Capital structure.
(The ultimate aim is to find the equation
relating rural wages to capitalisation. In
relating capitalisation to household
savings, the possibilities are that women
who do the conservation would be left
out. Savings of housewife may contribute to net aggregate Capital formation, but would not be
recognised as contributing to GDP. Whereas when the same thing adds to the income of a maid
servant, it would be recognised as contributing to GDP.)
The Odisha Food Processing Policy 2013 fulfils its own objective by intent only. A simple
calculation would show the optimal size of operation of utilities lies in creating balance between
Capital Cost and Operating Cost, keeping recycled (energy) as a parameter. Capital cost
increases according to a power law, whereas operating costs decreases (negative slope) as a
linear regression. The total cost is a U shaped curve. This shows that engineering given in the
photograph needs to be widely distributed, and would keep the size manageable by MSME.
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A Dryer based on Biomass Fuel Using Cookstove Technology for Food Processing,
Bakery, and Other Agriculture Produce
Most Food Processing units do not have many choices in Food Products or Process Design.
The former is dependent on climatic zone, soil and water condition (geographical terrain), and
other topographical features. The latter is dependent on food habits and culture. The only
choice left is scale of Operation, which is dependent on economic environment of the business.
The major cost consuming Unit Operations are washing, cutting (or shredding or grinding),
blending, and application of heat for cooking. Of these, the highest cost contribution is from heat
energy and labour (Skill) that is mixed in a workstation, as shown in the above photograph.
Intuitively, it can be seen that if wealth creation (capitalisation) is to be driven by aggregate rural
wages, then keeping the learning curve steep by having large and complex operations would be
counterproductive. This can be proved mathematically also. An outline of the proof is given
while discussing Skill Training in the Agro Equipment cluster
To give a sketch of the proof: steepness of learning curves is more dependent on facilities and
less on capability endowment of the learner. For example, the photograph shows a dryer
compatible to wood pieces as fuel. A substitute fuel based on a technology improvement is
pellets made from biomass dust, and a forced draft using 35 watts fan (fractional horsepower).
The facilities needed for learning control of heat for the equipment shown above is available in
every household, namely the cookstove. A complex equipment with great complexity of utility
A sectional view of Dryer
17
Inter Cropping in a Mango Orchard
and control schema can be mastered by only those few having access to expensive training
facilities. Scaled down facilities would blend process Skills of women workers with only marginal
investments; if prior skills can be used for exchanging labour power for wages, then the learning
curve would be less steep, partly due to self financing mode of learning introduced by on-the-job
learning, and partly due to the worker “chilling” out on her learning curve. The same philosophy
underlies MNREGA, which starts with an immediate exchange of prior skills and gradually
increasing exposure to jobs with more skill requirements. Whereas the MNREGA has high
governance costs, the enterprise strategy would have lower governance costs.
Unit Operations of Agriculture Figure 1 shows an important concept from a system’s (holistic) perspective. There are two
bifurcations, or recycle streams. One in Agro Processing Unit Operation, and the other in the bio
fuel value chain. Note that if liquid bio fuel is not produced, then the organic biomass from the
algae, or natural CO2 sequestering bio material, can be used directly as fuel. It can be shown
mathematically that if there is recycle loop in the system after bifurcation in a Unit Operation,
then system would reach steady state under certain boundary conditions. In other words, if Unit
Operations of Agro Processing is coupled (integrated partially) to Unit Operations of Agriculture,
it would stabilise Agriculture production and increase productivity.
Land use patterns, such as
inter cropping of stylosanthes
and turmeric is a result of
bifurcation originating in Agro
Processing capabilities that has
percolated (feedback) to the
farmland. Most farmers practise
some kind of product mix
based on their perception of
“information recycle” from the market. At least one member of the NAS farmers, Mr. Swaraj
Mohanty, has got direct contact with the market, which forms a major influence for the product
mix. The other major reason is labour availability, and a calculation of NPV (Net Present Value)
that is a predatory follower of net aggregate income of workers in the client organisation. Of
course, he does not compute labour power of clients as purchasing his goods, but since he sells
his produce in the local market (haat), the driving force for demand for goods are purchasing
power of those who come to market for buying goods for their consumption needs.
18
Exactly the same philosophy underlies custom hiring services that Mr. Mohanti (and all others in
the NAS sample) provides to the farmlands of neighbours. The quantum of services depends on
labour power engaged by clients, but it follows the equality constraint (Langragian) of allocation
of energy (liquid fuel) rather than any cost to benefit calculations. In other words, the cost
function is optimised by the energy allocation function. We therefore have a multifunctional
capability based on the Power Tiller / Tractor, even though each operation looked upon
individually is overkill in energy terms.
Power Tiller is overkill for threshing and winnowing operation, which does not require
more than 1 HP to operate
Transport by Power Tiller only usable for short distances
Power Tiller optimally used for tillage operations
Problem faced by Custom Hiring Services is availability of contiguous farmlands
A viable option only if it is a secondary income source. Its primary utility in own farm
Same services provided by Tractor and also by Draught Animal Power (bullocks) almost
under identical contractual conditions
Multi Functional Processing (MFP) by Power Tiller from Custom Hiring Services
19
Food Processing by Women SHG
Women groups depend on the haat for sourcing the raw material for their enterprise. Some of them come from the community that also sends casual labour workforce to the farms. However, the direct purchase of materials from farmers is not developed, as these groups do not have capabilities to understand futures contracting.
PRODUCT DESIGN REDESIGN AND DEVELOPMENT The Choices before MSME in Agro Processing/Food Processing Sector
From the Design Point of view of bio products, the MSME in Agro Processing/Food Processing
does not have much choice with Product Design. In this matter, the MSME has to depend on
support from Government in such things as Biotechnology, Tissue Culture, supply of seeds, and
inputs like fertilisers, etc. These advances in product design have to fit into traditional practises
in order that farmers can be organised into enterprises as per the intention of the Food Policy.
The MSME has choice in creating a blend of food products to grow and process. Workstations
are so designed that the MSME has flexibility in choosing the product to grow or process. In
fact, bio diversity and crop rotation is encouraged. Exactly what the nature of the blend of
products would be is dictated by access to the market and the information flow (feedback)
obtained from the market.
Inter Cluster Communication Pricing conveys most of the information in markets. In recent past, about four months ago, the
state government gave a lot of mobile sets to connect farmers to Regional Marketing Centres at
the district level, with a 100%
reimbursement of cost of information
(telephone bill). However, most farmers
are dependent on the pricing mechanism
of the local haat, and the mental model
they have about price trends.
The local haat according to Policy is the
collection centre for products, and is
dominated by Traders. These traders
frequently offer a futures contract to
farmers, and keep a hawk like watch on
movement of goods from the farm. If the
local haat and conveyance is well
developed, local traders are confined to
the auction bidding system at the local
haat with some supervision and
monitoring by government. Information is
20
concentrated at the Block level, on the occasion of providing inputs to the farmer, such as
seeds, fertilisers, saplings, warehousing, cold chain, and paddy procurement.
All engagements in the market are bound by subsidy. In effect, subsidy is the cost of ensuring
that buyer seller engaged in economic transactions follow democratic norms. However, it is the
collateral effect of price reduction (or increase in profit and net worth) that reigns supreme.
Although direct transactions by government would be a small portion of the volume of business,
and not all products have subsidised prices, it is sufficient to control information flow, monitor,
and supervise the engagements in the local collection centre (haat).
Emerging Opportunities for Choosing Blend of Products for Agro/Food Processing
As admitted in the Agriculture/Food Processing Policy 2013, the focus towards Agriculture
sector had been to strengthen the supply side. A demand side approach that is the current
focus of the Policy would necessitate a holistic approach by treating the production centres as a
market. It would build upon improving purchasing power for goods by increasing aggregate rural
wages. The scope is unlimited. 93% of the primary food products are not processed in the state.
30-45% of food produced is wasted.
The first signal to a farmer about an emerging opportunity is the study of price movement in the
local collection centres (haat). While a large portion of goods would be siphoned off by traders,
a small portion would be procured by micro enterprises, usually incorporated under SH
Cooperatives or informal groups under the aegis of a NGO/Govt. institution. The demand side
approach would build on these nascent efforts.
The role of Design Thinking to identify, act upon and track an opportunity is given below.
Spice Processing (Ginger) in Micro Scale-Cluster Approach
Primary Processing Grinding Solvent Extraction
Spice Processing in Odisha is an emerging industry. Majority of the spices is sold in raw form, with proper packaging. The players who have entered the Spice sector are multicrore industries by building on Brand Equity of spice and diversifying to other Food Products.
21
MSME CAPABILITY DEVELOPMENT The Odisha Food Processing Policy 2013 has kept an ambitious target to raise food processing
from 0.7% to 10% by 2017 (next three years), and 25% by 2025 (next ten years). What the state
Government is keen to ensure is sufficient capitalisation (investment) to achieve this target.
Centre’s commitment under NMFP to the state barely touches Rs 10 crores. Therefore, the
state Government hopes to tap the corporate sector for funds.
As such the FDI pie is not suitable for this sector. It is well known that FDI funds had gone into
infrastructure projects, such as steel, mines, construction, and power. The MSME on the whole
had not been a factor in that growth. There had been enormous increase in income from mining,
but it was a financial growth, and a jobless one. It did offer jobs to labour, but that did not
convert to growth of enterprise (MSME), and consequently, when the sector went bust, workers
simply returned home. (Migrant Agriculture workers stay on with their families even if there is no
work. Maybe a primal instinct to be near food source has evolutionary stability.)
Against that experience, the Agriculture and Food Processing sector has always been based on
inclusive growth. Strong positions taken by communities against selling land to industries like
Vedanta and Posco show there was a latent demand for “inclusive growth or not at all”. While
inclusive growth has become rather clichéd, the fact is that investors would be attracted by
extant capabilities rather than by a latent demand. The former would create demand (for goods)
while the latter is so much grist to the mill for populist statements and attracting votes.
From the Design Point of View, it is those extant capabilities in functionality of Unit Operations
that are important, as this would convert to wage income and demand for goods. The review of
workstations show such capabilities, honed in small clusters and passed down through
successive generations. Hitherto, it has been too small to draw attention of Policy planners. Its
protection and development so far has been a cultural issue. Food Processing is kept alive
through institutional mechanisms such as Delhi Haat (in Delhi), Ekamra Haat (in Bhubaneswar),
the corporate involvement in Hotel Industry and Tourism, and lastly those TV chef programmes.
These are the “temples” that have been slowly edging out the Religious temples. Whatever view
one may take of it, the existence of a vibrant Agriculture (Agri + Culture) and Food Processing
will depend on Postmodernism influence on culture. The econometrics of Postmodernism is that
an investor has to pay for the cost of coordination in order to get its ROI. Using a parametric
analysis, it is possible to show that most economised means for obtaining such coordination is
to enhance Design Thinking in the eco system of MSME.
22
The example of Mr. Swaraj Mahanti taken from this NAS would illustrate the manner in which
MSME develop capabilities, and as an emerging opportunity, what can be done to enhance it.
The Narrative: Mr. Swaraj Mohanti’s main trading point is the Ranpur haat. Besides the produce from fruit orchards, mangoes and banana, every year, he decides what else to produce by intercropping. Vegetables are sold in the local Ranpur Haat, whereas fruits have long term arrangements with wholesale points in Bhubaneswar. Smaller traders (retailers) who take produce of smaller farmers to sell in the haat oftentimes use the (institutional) Brand Equity that he has developed in the local market. When deciding the current year’s product mix, he forms mental models from all information about all the paths taken by all traders and farmers, i.e. a cluster map. These are time robust maps that capture the essence of events over a time period, especially price movements of different products, patterns of demand supply gaps, Policy, behaviour of officials, social and lifestyle context of workers and consumers and visiting traders, technologies, and so on.
These maps are not vocalised, nor charted in the form of graphs and equations, but participation in the local market provides a description of the maps that helps in guesstimating blended costs. For instance, the high price of labour has dissuaded him from growing vegetables, and would be resumed after making certain capability improvements, acquisition of skills, and functional designs. According to him, these steps may need fresh investments (equivalent of capitalisation as the money must come from current business).
We paraphrase the narrative in the language of Design Thinking, in terms of the functional
designs (Unit Operations) inhering in the flowchart of Figure 1. The description of workstations
(photographs) mentions a few, such as grinding, threshing, dust separation, combustion,
extraction, multi functionality. All of them can be quantified by using energy units as the Design
Parameter. Analysis of maps, graphs, and charts using the Design Parameter would lead to
identifying opportunities, and give preliminary estimates about feasibility. A rigorous verification
of feasibility would need assessment of all components of the NAS checklist given in Table 1,
but a fairly accurate validation can be made on the basis of any one Design Operator.
Figure 1 shows the bifurcation to two product streams in Agro Processing operation, one going
to the cattle feed market, and another to Food Processing market. To cater to both the markets,
the MSME would have to develop functional expertise for two product streams that are distinctly
different from each other, mainly by hiring Skill or by training of workers. Bifurcation enables
engagement in local markets for selling two products. Feedback from sales (price, preferences)
increases separation between bifurcated functionalities so as to consolidate sales. Every time
information loops iteratively, the separation between functional designs increases. Repeated
bifurcation develops multi functional expertise in the MSME Unit.
23
Raison d’être of developing multi functionality by bifurcation is to enable optimisation of
Resources available through trade or engagement. But this bifurcation comes about due to cost
(funds) recycle to the business obtained from pricing and engaging in trade. The objective is to
dynamically maintain a blended cost that would balance revenue and ‘expenditure + profit’, so
that the enterprise survives for the next Budget period, (or product lifecycle = several Budgets).
For a long time bifurcation was not clearly understood, although empirical mathematical
formulations of it were used for analysis of market segment data, science and engineering,
technology, economics, and social sciences. The bifurcation must lead to distinctly different
entities, and form ensembles when these entities are clustered. Bifurcation is the basis for self
reproducing organisms and assertion of species interest by adapting to the environment. This
underlying philosophy for survival of enterprise in the marketplace is captured by photographs.
The photograph shows an effective way of optimising Resources use by grafting. Exactly the
same process underlies “grafting” of functionality to achieve multi functional capability for
optimising Resources available through engagement and trade. The necessary conditions for
bifurcation optimisation are (a) engage in trade and recycle funds, i.e. surplus of revenue over
expenditure, (b) having access to the information processing capacity of markets, (c)
experiment by adding functionality. (A similar instruction given to American soldiers is: (a)
capture upper ground (b) stay in touch (c) keep moving). Calculation is needed to check if there
is growth (increase in net worth) or retardation, but otherwise it is a simple iterative process.
Fractals in Nature and Architecture (illustrating bifurcation)
Two Branches Three Branches Four Branches Sagrada Familia (Gaudi)
Trees branch out to capture sunlight and air. The shape of the tree can be produced in a computer by keeping a record of the trajectory by “recycling” fractal shapes. Fruit tree canopy architecture is practised by grafting to form two, three, or four branches.
The use of fractals in architecture of Sagrada Familia, a church, was constructed by Antoni Gaudi (1842-1926). He built tall structures of bricks, masonry and concrete without columns
24
Emerging Opportunity Using Energy Design Parameter
Since Unit Operations can be quantified by Energy units, this gives a way of reducing the
number of experimental iterations to create optimal conditions for growth of MSME. Examination
of Figure 1 shows that if the functionality added to the MSME capability improves use of
“recycle” energy, then there is maximum likelihood of ensuing multi functional capability being
optimal, subject to condition that the functionality would be producing a saleable commodity.
(Conditional optimality is solved mathematically by using Lagrangian or Bayesian functions.)
In general, it means that in following the dictum of Food Processing Policy 2013 of reducing
farm wastage, energy conservation measure should come from a process stream. This is an
equality constraint of objective function to make blended cost of the product mix equal (or lower)
than the blended cost of the same product mix in the market. In other words, the optimal costing
based on market returns of product mix lies on the curve followed for optimal energy
conservation. (Mathematically, max φ(X), subject to f(X) = 0, φ is objective function, f is the
energy conservation constraint). The calculation for optimal blending cost using energy as
Design parameter applies to any source of energy, whether solar, fossil fuel, or bio mass.
This strategy leaves out solar energy and energy obtained from any fuel procured for meeting
energy needs from the computation of optimality, since it is not a “recycle” energy drawn from a
process stream. One should not be tempted by the 70% subsidy for electricity generation with
solar energy, as solar energy is for the power companies who sell power to the grid. Using this
power in the computation of cost optimisation is likely to result in cross subsidisation that
ultimately benefits the power company supplying power to the grid.
In comparison, it must be stated that fabrication industries use weight as Design Parameter.
Saving scrap, or minimising scrap generation, has maximum likelihood of converging to optimal
blended cost for all products.
The above procedure is for determining the Design feasibility for making a product or adopting a
process in the eco system of the MSME. It does not say that the product made under this
procedure would sell. It must be remembered that this is a dynamical balancing method, and
does not apply for dead stock. Accountants generally provide a place for such stocks; so that it
does not interfere in the costing process, such as amortisation, write off, transfer of title, etc.
Noting that it is an experimental iterative procedure, it can be accomplished in a virtual
environment, or a consultation workshop, for purpose of Market Competitive Study (NAS list 7).
25
Market Competitive Study for Design Distinction Methods outlined above using energy units as Design Parameter for finding competitive blended
cost for product mix of MSME based on saleable goods can be generalised to all opportunity
areas given in Table 1 below. By competitive costing is meant that the blended cost in the unit
would be same (or lower) as blended cost for the same product mix in the market. To make a
market competitive study, one could use other Design Parameters like weight, cost, or bytes.
Table 1: The Design Matrix of Design Thinking
DESIGN THINKING
Operators (Cluster Mapping Tools)
Opportunity Area (Cluster Level, Major)
Opportunity Area (Unit Level, Minor Project)
Design Information Forecasting Assessment
(NAS 13) Inter Cluster Communication
(NAS 1) Product Design Re Design Product Development
Interactive Design and Strategic Collaborative Design
(NAS 2) Tech Modernisation and Collaboration
(NAS 3) R&D Directions for Future Development
Incremental Design development
(NAS 15) Improvement in Process of manufacturing and productivity
(NAS 5) Workstation and Tooling
Functional Designs to Reduce Adoption Costs
(NAS 14) MSME Capability development
(NAS 7) Market Competition study for design advantage and distinction
Space Innovation (NAS 18) Manufacturability, serviceability, manufacturing process
(NAS 4) Process Innovation and Related areas
Quality Function Deployment (NAS 16) Market Share and Profitability
(NAS 19) Value Addition
Enterprise Social Responsibility
Design to Cost (NAS 8) Training and Skill Upgradation
New Product Introduction (NAS 10) Infrastructure and Capability Enhancement
(NAS 9) Packaging logistics and Storage
Lean Practises (NAS 6) Ergonomics and Environmental Factors
(NAS 17) Reduction of Wastage, Energy, etc
Graphics Design, Linear Perspective
(NAS 12) Visual identity and branding
(NAS 11) Exhibition/Display
26
To use Table 1, it is important to assign a measure of the “whole”. In Food Processing, the
“whole” is easy to determine from studies made by nutritional experts, or army rations, food
served in hospitals, midday meals, ICDS anganwadi, and many places. The most accepted
definition used previously was poverty line based on calories intake. This has since been
discontinued, since it was problematic to convert it to a Blended Cost of the wholesome meal.
Put differently, the Blended Cost had variance, and factors that were cost determinants were not
knowable. Therefore, a Benchmark Blended Cost was fixed based on income, making it easier
to assess the budget needed to service the BPL population. The same principle can be used for
heuristically fixing a Unit Measure for product mix that is “whole”. For availing government
subsidy or its procurement services or for selling at controlled prices fixed by government, it is
safest to use the same definition of “whole” used by government. A little bit of literature survey is
needed, such as reports of World Bank, all UN agencies and others.
Assuming that the ideal product mix (with costs) perfectly matches customer needs for a
wholesome meal, it is assigned Unit Measure to form Design metric (D) = 1 for a 100% match.
When the Unit Measure of D = 1 is expressed in cost terms, this would be called the Unit Cost
of the product mix. Actually, the Design metric is D < 1 is acceptable, and when expressed in
cost terms would be the Unit Cost. However, the ideal standard design can be used to analyse
manufacturing process and productivity.
This Unit Measure D =1 is split into fractional dimensions of the whole, and produced in a
“workstation”. When all fractional dimensions from different workstations are put together, D = 1
is reproduced. Deviations of the fractional shape Di from the design output is the error. All these
errors add up to produce the overall error.
Exactly the same procedure is followed for adding fractional cost contribution (fractional value
addition) of the workstation to the Unit Cost of product design D. A cost variation could have
many sources, such as materials, skills, minor changes in procedure, time taken for a job, and
so on. (Mathematically, errors or cost variation are normally distributed. Addition of blended cost
(or comparison of two blended costs by subtraction of mean) is not an arithmetic operation, but
is done using statistical functions. Addition/subtraction of statistical (stochastic) variables is
addition/subtraction of area under the curve.)
A fraction of D = 1 would be a fractional dimension, and the operation that produces the
fractional dimension would be called Operator (column 1 of Table 1). In the case of MSME, the
Operator is experimentally accomplished, in small doses at a time, using an iterative process.
27
Operators can also be mathematical expressions. In either case, outcomes are to be mapped. If
Mathematical Modelling is preferred, then Operators are Mathematical functions. These apply to
Technical Solutions of engineering and science, such as designing a chemical or biochemical
process. But the bulk of modelling is done experimentally by trial and error. Workstations are
pictured as adding fractional dimensions to the product mix using.
Fractals are special class of Operators that feedback a fraction of the “whole” (product design)
to the system (workstations of MSME) to get the next outcome. In Design, if an iterative process
is used by feedback of the outcome of the previous iteration, then fractals operations are used.
The assembly of fractals is called an ensemble. A random collection of fractional dimensions
cannot be called an ensemble. To form an ensemble, the fractals must have a defined
relationship to the whole, like relationship of individual pieces of clothing such as shirt, (or pant
or shoes) has to a costume. To define relationships, rules of the game, or axioms, are needed.
Whereas in general a wholesome product mix with D = 1 can be assembled from different
fractals produced in a cluster, the workstations of a MSME all put together would be producing
only a fractal. Clearly, to determine the Unit Blended Cost for Agriculture, Agro Processing, and
Food Processing, the local Haat would be a much better place than the workstations of the
MSME to form the Unit Measure of Design metric D.
Use of fractals makes it much easier to determine Design feasibility, such as establishing gaps,
determining substitution designs or complementary designs, and cost tradeoffs. An example of
trade-off is additions of feature designs to product mix to fill a gap in client system; multi
functionality (features) lowers adoption costs and MSME provider can increase sale price.
Custom Hiring Centres of government and private, which the farmers in this NAS practise, is a
cost trade-off operatioanlised (incentivised) by multi functionality.
The overarching simplifications of studying a design issue by fractals is (a) phenomenon called
“self similarity”, (b) applicable across scales, (c) simpler mathematics once the fractal dimension
is determined, (d) adaptive to the environment and (e) recursive. For instance, take the 80:20
law, which arises from a fractal dimension. The 80:20 law simplifies analysis, as 80% of
problems can be addressed by a subset of 20% of variables. 80% of Resource allocation is for
20% of people (or workstations, functions, or any of the variables of column 2 of Table 1. Once
the top 80% is removed from analysis, the balance 20% would can also be divided in the 80:20
ratio. Knocking off the 80% of the 2nd iteration, the balance would divide in ratio of 80:20. This
can continue no matter how many times the iteration is continued.
28
EMERGING OPPORTUNITIES BY USE OF FRACTALS To use fractals and the advantage it gives to control dynamical situations, such as market and
ROI, there are certain necessary conditions, given as follows
A feedback control strategy is used for deciding any remedial action
The region in which analysis is carried out is an open set. This generally means that
one must forget the “initial state” of the system. (Governor Raghuram Rajan put this
succinctly when he said that Banks should not recapitalise losses of pioneers and
founders)
The system should exhibit ergodicity. This generally means that one should follow a
market system that has inherent balancing characteristics and no imperfections like
gender bias, or social discrimination, or monopoly like cartels. An ergodic system implies
that statistical analysis can be used to make projections to future without fear of bias.
The success of MNREGA is attributed to a couple of axioms like allowing equal opportunity for
men and women, APL and BPL, and remaining within limits (boundaries) imposed by the social
group, such as travel limits of women in search of work. This principle applied to a MSME
means that ESR (Enterprise Social Responsibility) privileges must be the same to both regular
employees and casual workers. The latter generally outnumber the former in ratio of 5:1 to 10:1.
The most flagrant violation of this rule is from the government itself.
In the case of Food Processing sector, the extended ESR calls for using the services of a
collective agency like a NGO (Civil Society) to span the whole length of the value system given
in Figure 1. Oftentimes, MSMEs of Agro Processing/Food Processing sector are likely to round
off what is happening in Agriculture, thereby imposing a boundary, and defining the open set too
narrowly. This creates difficulties when deriving measurements from the local haat.
The overarching advantage of strategising a Remedial using fractals is that one need do a small
thing to make a large difference. Some of them are given below.
Training and Skill Upgradation 1. Matching the capacity of the primary (e.g. MB plough, Disc Plogh) and secondary tillage
(e.g. cultivator, rotavator, power tiller) to minimise idle time of each machine
29
Dry Seeder can be Used with DAP (Bullock) and Power Tiller
2. Tractors are not in their peak efficiency during primary tillage operation during summer
plighting and ploughing after early monsoon because tractors are diverted for transport
of construction material
3. Tractors are operated by semi skilled operators, who are not aware of best maintenance
practise during on road and off road operations
4. Tractor company’s service outlets are few in number, mostly located in urban areas.
Therefore these tractors are maintained by semi skilled in automobile workshops located
in suburbs who are not aware of tractor and power tiller maintenance
5. Drying done on the municipality / village / NAC pucca road resulting in crushed grain of
poor quality, rain affected drying, with family labour results in accidents due to fast
moving motor vehicles
Manufacturability, serviceability, manufacturing process 6. Dry seeding of paddy is
the best method for
minimising cost of
cultivation of this crop
7. Summer ploughing is must
in this method with use of
pre and post emergence
weedicides. Labour
requirement is reduced by
a third in this method
8. Spraying by power sprayer can
control fast propagating plant diseases
and pest (brown plant hopper, swarming
caterpillar and yellow vein mosaic
spreading white flies in gram.) This
sprayer is more effective due to the
dislodging effect of pest by the air blast
produced during spraying
30
Post Hole Digger for Orchards
Training in Post Harvest Management
9. For machine transplanting, puddling should be
done to a depth of 7.5 cm in the early part of the
monsoon with a settling period of 2 to 3 days
10. Seedling transportation and transplanting is a big
problem with labour cost at Rs 250 per day
11. Transplanter need seedlings of 21 days ± 5 days
old seedling and can be transplant maximum 3
acres per day. Therefore this machine needs
staggered nursery raising with maximum of 240
m2 per day
12. Matching the capacity of vertical conveyer reaper
and axial flow thresher in case of paddy and
groundnut digger with groundnut thresher is important from the point of view of best
utilisation of machine capacity
Infrastructure and Capability Enhancement 13. The inputs in Agriculture such as
seeds, fertiliser, pesticides, and irrigation
water has become costly and scarce
resulting in delayed supply and black
marketing which affects production
process
14. Bi products to be utilised properly. Regular
training to be provided
15. Agriculture clusters, Agro Processing and
Food Processing clusters need a CFC with
primary membership of private Custom
Hiring Centres to drive corporate formation
31
CONCLUSION: DESIGN THINKING FOR SHAPING EMERGING OPPORTUNITIES From Design Point of View of manufacturing, it is useful to make three conceptual deconstructs
of an Enabling Technology, viz. Technology, Skill, and Protocols as given in Figure 2.
Figure 2: Conceptual Distinction of Elements of Enabling Technology
A colour code is used to say that the three elements are always found together, i.e. a property
called confinement Red + Yellow + Blue = White, borrowed from Physics in describing
behaviour of Quarks. For example, a Skill institute like an ITI or engineering college (or NID)
would have laboratories and workshops, and students follow protocols to carry out an activity.
The concept applied to Design Thinking without loss of meaning, deconstructs it as follows.
Table 2: Deconstructing Design Thinking into Enabling Technologies
Measure Deconstructs of Design Thinking Operator
Technology Design Space Interactive Collaborative Design Red
Skill Set Enterprise Social Responsibility (ESR) Skill Development Yellow
Protocols Cloud of Points (Blending Processes) Design to Cost Blue
ENABLING TECHNOLOGY
Old Technology
Old Protocols
New Protocols
Old Skill Set
New Skill Set
New Technology
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Raphael’s “School of Venice” blends philosophers, mathematicians spread over several generations.
It illustrates the meaning of “Cloud of Skills”, e.g. teachers/students “Square the Circle”, (calculating the value of pi Π), similar to combining algorithms in Cloud Computing in the age of Internet and Information Technology.
The taxonomy of terms used in Table 2 is given below for quick reference (cf Gantayet, Oct
2012 where some of these terms have been explained in some detail).
Taxonomy
Design Space: is defined in the web as: “The entire range of all independent variables.
Measures or amounts that is directly controllable.” Since such a definition becomes humungous,
Design Space is defined as goal oriented and measure preserving. Example in the web:
optimisation of variables under constraints of Resources to achieve quality, or cost. The NIFT
(National Institute of Fashion Technology) describes Design Space as blending old technologies
into an emerging grey area. This definition is probably to attract Skill from various
specialisations to do M Tech in their institute. Design Space is bounded space and quantifiable.
(Definition of Design Space given by this Design Expert is to make it measurable (quantifiable) in terms of a measure that best describes the Emerging Opportunity Area of Figure 3: Keeping Track of Emerging Opportunity Using Statistical MLE
This method of forming estimates of parameters (like price or cost or income or market share)
based on historical data using normal distribution as a MLE is well known, and is given in any
standard textbook on marketing and economics. It has severe limitations, as it assumes a
stationary population. Forming estimates in a dynamic situation can be very tricky, and its
analysis is fairly complicated. However, the advantage of dynamical models is that it can be
used pro actively, and provides a way for the MSME entrepreneur to act and not react in order
to survive the rough and tumble (global recession) of the market place.
. As a further simplification to avoid confusion, we have used only two measures,
Unit Cost and Skill Sets. They can be converted
by laws of Table 2, similar to converting calories
to Joules using first law of thermodynamics).
Interactive Collaborative Design: is well defined in Design
Clinic Scheme Guidelines, where pages and pages have
been written. (See Raphael’s School of Venice for concept).
Enterprise Social Responsibility: is the benefits given to
any worker engaged by MSME, whether employed or not
33
Industry Average
Weak
Competitor will be
swallowed up
Product Life CycleCompetitive Positioning
Strong
CompetitorFirst Mover, or
Predatory Follower
Last In …
Design A (Old) Design B (new)
Design C (new)
Design D (new)
Product Life CycleRegeneration defines Design Space
DESIGN SPACE (UNDER THE CURVE)
Skill Development: is the process of imparting Skills by training, on-the-job learning, project-
based-learning; usually in one or more peer groups; mentoring is part of the process
Cloud of Points: is the description of the shape of the surface of any object, or the description
of the features of a design when applied to a 3D object. Meaning of cloud is the same as that
used in cloud computing; as an ensemble of skills, methods, and processes to obtain a desired
objective
Design to Cost: is manipulating Design to achieve product’s functional and ergonomic features
within a pre determined cost, or affordable cost, or a cost that maximises value to customer.
Techniques to use Design Thinking for shaping an emerging opportunity are to make the MSME
Unit capable of computing and using a MLE (Maximum Likelihood Estimator). The MSME
should be trained to use a MLE, which if reasonably accurate, would identify and give shape to
an emerging opportunity and keep track of Emerging Opportunity.
Figure 3: Keeping Track of Emerging Opportunity Using Statistical MLE
This method of forming
estimates of parameters (like
price or cost or income or
market share) based on
historical data using normal
distribution as a MLE is well
known, and is given in any
standard textbook on
marketing and economics. It
has severe limitations, as it
assumes a stationary
population. Forming
estimates in a dynamic
situation can be very tricky,
and its analysis is fairly
complicated. However, the
advantage of dynamical
models is that it can be used
34
pro actively, and provides a way for the MSME entrepreneur to act and not react in order to
survive the rough and tumble (global recession) of the market place.
Motivation behind Design Thinking is to use only one of the elements Table 2 to form the Design
metric D, which can be Skill Sets, or Procedures, or Technologies. As mentioned above, these
three act as constraints (Lagrangian) for finding the optimal conditions for growth of
MSME/cluster. In Agriculture/Agro Processing/Food Processing, where one has to perforce rely
on distributed technology, Training (Skill Development) has been the method of choice. This
training is Performance Based, hands on, practical training, with theory being taught through
demonstration type of lectures with very simple picture formats (graphs, pie charts, histograms).
Once the background has been formulated, i.e. boundaries have been created as given on page
28 by the Capacity Building Institute (Design Institution or Resource Cell as per the Odisha
Food Policy 2013), and linkages established, the addition of fractals in incremental doses would
result in creating an “envelope” curve given in Figure 3 above. The Y axis is the cost function.
Normally, the real time curve of cost vs time is a crazy zig zag curve that is so often published in
statistical reports. To determine the cost function, slopes of the zig zag curve (cost function)
over a defined time period, say 12 months, is taken and a frequency table (histogram) made.
The typical statistical distribution is obtained by drawing the smooth curve of the histogram.
Figure 3 (top) shows how such smooth curves (normal distribution) are added. The “envelope”
should follow the industry average, or be a predatory follower (Figure 3 bottom).
Advanced Analysis by Researchers Inside each baby curve of a new Design is the trajectory (phase space) of the Design
Parameter. The baby curve of Figure 3 (top) is a function of the topological map of fractal
operator, whose mapping is rather complicated, and can be analysed only in a computer. This
curve would show many bifurcations. This can be safely ignored in training MSME, or to the
average Research scholar in the field of Agriculture and Engineering, unless the analyst is very
proficient in Maths, computer simulation and numerical methods.
Most Researchers use multivariate analysis called Response Surface Methodology without the
core assumptions of Design Thinking of Confinement law to plot surfaces. The connection
between Confinement law and trajectory (maps) of fractals is the property called “dense”
periods. This means that all trajectories (maps) of the Design Parameter measure of Skill Sets,
Procedures, and Technologies (say energy) would approach close to one another, and are
35
Apply Bayes Rule
• Set up problem as P(R|N), i.e. Remedial taken up if MSME unit forced to go for a New Product– R: Remedial, N: New– P(R|N) = [P(N|R) x P(R)] / [P(N|R) x P(R) + P(N| not R) x P(not R)]
– P(R) = 0.1, P(not R) = 1 - 0.1 = 0.9– P(N|R) = 0.7 (as found from studies of Business Incubation
scheme, and study of requests by MSME units for Design Projects)
– P(N| not R) = 0.3
• Therefore substituting numerical P(R|N) = 20.6%– Chances are good as per PLC curve that Remedial Design
would self-sustain, since it is higher than 16%
bunched around two fixed points, called attractors. Whereas Response Surface Methodology
assumes these points to be fixed in time, (do not shift with time), attractors shift with time due to
small perturbations. Response Surface Methodology cannot analyse dynamical balancing, and
does not require systems to exhibit ergodicity. However, Response Surface Methodology can
be adapted to form a time series using Bayesian statistics, or sequential equilibrium, and
dynamical balancing (equilibrium) computed using Bayesian statistics.
One example of sequential equilibrium is PERT, which assumes normal statistical distribution.
Most practical Researchers, like practising engineers, entrepreneurs, should start by using
PERT as a analytical tool to spot opportunities, especially gap filling. These should be backed
up with intuitive description of what is actually happening, or should happen.
The illustration shown below gives how Bayesian statistics can be used to form a time series,
i.e. motivate a future course of action. To analyse time series data, often used for trend analysis
and forecasting, Researchers, especially economists, agronomists, plant physiology,
biotechnologists, and biologists studying genetic engineering have to graduate to the next level
such as Game Theory, Evolutionary Game Theory, and Rational Choice Theory in the study of
dynamical situations.
Suppose we want a MSME or client to adopt a Remedial. Bayes rule tells you what to do to
improve chances of adoption of the Remedial by conditioning probability of adoption with
another event, such as enticing the MSME to go for the Remedial by tempting MSME with a
New Product Design.
36
Workshop Report
Interactive Design Research—Band 2
Of
Bhubaneswar Agro Processing Cluster
Sponsored by
“Design Clinic Scheme, Ministry of MSME, Govt. Of India”
Under an Agreement with National Institute of Design, Ahmedabad, the Implementing
Agency, and Central Toolroom and Training Centre, Bhubaneswar
Prepared by
Dr. N. P. Gantayet, (PhD) and Prof. S. K. Nanda (Retd Prof OUAT)
November 2013
120, Madhusudanagar, Bhubanesar-751001, Phone 06742390311, mob: 09937631559
www.thermo_orissa.com; e-mail: [email protected], [email protected], [email protected]
1
BROAD DETAILS Cluster Name: Bhubaneswar Agro Processing cluster
Design Experts: Prof S. K. Nanda
Programme Band: Band 2
INTRODUCTION While the NAS had covered 9 contract farmers, the number of participants to the workshop was
around 15 on the Day 1 and around 7 on Day 2. Day 1 of the workshop was held at cluster
level, while Day 2 was held at CTTC.
Day 2 of the workshop was held simultaneously with Day 1 of the BBSR-CTC Agriculture
Equipment Cluster DAP workshop that was running concurrently with the DAP Agro Processing
cluster. Besides MSME equipment manufacturers, participants in both the workshops included
other focus groups such as academy, M Tech students, Design Experts, organisers CTTC and
finally observer from NID. This day’s event was widely reported by the media. Thus, the
coverage was of a wide spectrum of stakeholders, including the public.
For sake of brevity, this day is referred to as the “stakeholder consultation” in this report.
Whereas different newspapers have reported aspects of the DAP Stakeholder Consultation, all
reports converged to Skill Building as the means to improve Design competency of MSME in the
region. Earlier on the same day, a group of around 41 UG engineering students were given an
exposure seminar on Computer Aided Engineering design with focus on Unit Operations of
Agriculture, Agro Processing, and Food Processing to highlight the esprit of Skill Building.
The purpose of converting one day of the DAP Workshop to a stakeholder consultation was to
note the event time series in the next fifteen days following publication of media reports. While
this made the design of the workshop on this particular day amorphous, it structured the DAP
workshops of Days 2-5, and focus group discussions (FGD) of students and academics. The
“media event” provided a context for design projects of DCS (student project and professional
design project), and gave a lead to subsequent Awareness programmes under Design Clinic,
Entrepreneurship Development, Skill Building, and Technology adoption. It also identified
several Research issues in engineering and Management; for e.g. drawing up a Business Model
with Design at Centre, and use of PLC curve to identify workstation Redesign.
2
DAY 1: A CONCERN FOR PRICING The picturesque place of Ranpur just 60 Kms away from CTTC is an ideal place to get away
from high tech machines and administration.
Little wonder that the major part of the Design issue discussed off the dais was on eco tourism
for this cluster being encouraged by Food Processing Policy 2013. However, exposition from
the dais has a technical flavour and is given below.
This workshop did not need a LCD for displaying photographs to participants. Shri Sibasis Maiti, GM, CTTC explaining about the Design Clinic scheme in view of the fact that farmers going in for Value Added products would get finance and subsidy under the Odisha Food Processing Policy 2013 by converting to MSME.
Speakers on the dais Shri Swaraj Mahanti Shri Ambuj Nayak
Prof S. K. Nanda Dr. N. P. Gantayet Visual Acuity Transect
3
“Price of anything is the toil and trouble of acquiring it.” Adam Smith
The dominant theme of the Agro Processing workshop was pricing of Agriculture goods. This
was prompted by the sudden price rise of Horticulture products after cyclone Phailin had struck
Odisha. In the photograph of the walking transect of the farm by the august body, one can see
uprooted banana plantation in the background.
In markets, pricing conveys information. The temporary dislocation in the supply chain had seen
prices of potato and vegetables spiralling. Like any communication, Price could have different
meanings to different people. Interestingly, the 1999 super cyclone that had struck Odisha with
greater devastation and massive destruction of crops, livestock, and people (10,000 died) had
not witnessed such price rise in commodities and vegetables. Although this was not articulated
during the discussions, this fact has a bearing in post modern economics. In the gathering of
farmers for example, opinion was sharply divided between increasing productivity to encash on
price rise in agriculture products and value addition to counter rising cost of inputs like seeds,
fertiliser, and labour. The debate was inconclusive on that day, as it is even now. However,
discussion on price instability provides an ideal context for introducing design tradeoffs.
Address of Speakers
Shri Ambuj Nayak welcomed participants, and requested Shri Sibais Maiti, GM CTTC, to make
a formal inaugural address. Addressing the gathering, Shri Maiti complimented on the beauty of
the surroundings. CTTC was a Centre of Excellence for precision machining, but as far as
Agriculture was concerned, it had to explore in which way the cluster would interact with them.
Prof. Nanda took hold of the proceedings from then on, steering a participatory discussion
between participants and panel (dais) members. Some very obvious faults in mechanisation
was reviewed, especially use of Power Tiller in operations for which it was not designed such as
primary tillage. In a short time the discussion moved onto pricing.
The primary cause of price rise was lower production due to unavailability of labour.
o By unavailability is meant that labour was no longer available in the old rates.
The many fold increase in labour rates, five to six times, made farming unviable.
o Rural workers found it not necessary to put in required man hours because of
availability of rice at Rs 1 per kg and higher income despite working lesser hours
4
This state of affairs (inflation) was punishing to farmers, since benefit of increase in sales
price of commodities mostly went to the middleman
o Not many farmers had proper information about the distribution of price in the
value chain, or access to information.
o There was no mechanism to stabilise prices in the medium term for sufficiently
long time for farmers to plan their production and get a decent ROI
The policy of the government was at fault, since they failed to exercise any control of
prices in the supply chain, investments for cold storage, and procurement prices
o Remedial measures included investments in refrigeration and preservation (cold
storage), which in Odisha was highly inadequate.
o Prof Nanda cited using cold boxes of modular construction using sandwiched
poly insulation between SS sheets to save on power when stocks were low
Economics of paddy (wheat, maize, ragggi, and staple crops) was such that it satisfied
inelastic demand, making it possible for government control over its production, pricing,
subsidy and procurement. Horticulture products, meat, eggs and fish, had elastic
demand, and greater price fluctuation. There was no control by government.
They fetched more value than paddy, but needed knowledge based workers. In general,
horticulture products (and livestock) needed more care and constant attention.
o Prof Nanda said that paddy and staple crops were easier to produce than
horticulture products, since they were less affected by pests and plant diseases
o Pest control by use of pesticides in horticulture needed appropriate equipment,
so that pesticide reached underside of leaves. General spraying was not effective
o Weeding when the plant was not very high needed smaller machines that could
be used between rows. Use of bed raiser by tractor was not an effective solution
o Mechanised plucking was out of question for most horticulture produce
Prof Nanda strongly advocated “value addition” in the farm itself. This was a bit difficult
for farmers, who were reluctant to change old practises and update technology.
o A benefit of mechanisation was that it encompassed a technology upgrade
5
Processing Equipment for value addition such as dal polishing machine was not costly,
(in thousands) while at the same time it provided a 20% increase in the sale value
o A hand operated machines were available for most processing operations
o Most important steps of processing included grading, sorting, preservation, and
packaging
In response to Prof Nanda’s opening speech, Mr. Swaraj Mahanti gave a diametrically opposite
view to tackling the pricing issue. He advocated proper information flow in the supply chain so
that price of goods in wholesale and retail points were known to the primary producer. The
means to counter a skewed pricing structure and the exploitation of farmers by the middleman
was to increase productivity. If wages were to increase, there should be commensurate
increase in skill, especially in operating equipment and mechanisation.
During discussion, Prof Nanda said that farmers had to speak in a unified tone, which was
lacking among farmers. There were instances when farmers refused incremental benefits under
various schemes because they could not agree on how incremental benefits would be shared.
Joining into the discussion, Dr. Gantayet said that the lack of standardisation of Agriculture
equipment by a standardisation agency of BIS would lead to disagreements on pricing. The
consequence of lack of standardisation led to the following
If there were standards, then cut off price for standard features (functionality) would be
fixed, say by a committee. This would quantify incremental benefits due to any additional
feature by manufacturer, and form a basis for agreements on pricing.
o For example, the Swastik Farm had an 11 KV feeder right at the doorstep. This
meant that it could draw power for any processing industry.
o However, most of the power needed in the diary did not exceed 3 KW, and there
was sufficient roof space to get that from solar power. This would be
complementary to grid power.
o It would improve reliability, since maintenance of solar power would be in the
hands of the farm, whereas changing a fuse of an 11 KV substation in a rural
feeder would take best part of the day if safety protocols had to be followed. If the
substation happened to be at the end of the feeder, where rural feeders generally
are located, quality of power and availability would be atrocious.
6
o Technology had improved wherein it was possible to blend power from two
sources, one AC and one DC, or two AC in the loads needed in the farm and for
processing. Biomass availability being good in horticulture, electrical power was
not needed for energy intensive operations like boiling and drying.
Agriculture and Food Processing Unit Operations being non linear, only the performance
should be specified to the equipment manufacturer, such as throughput, product quality,
and features (functionality)
o Most equipment indentors provide dimensioned drawings with the assumption
that manufacturers would give a verifiable costing. In absence of standards, and
also performance guarantees, manufacturers can easily sell a “lemon”
o Equipment Manufacturers, especially fabrication and machining, need drawings,
and these are provided by detailed designers. Without drawings, even the most
sophisticated machining, like CTTC, would collapse. (Corroborated by Shri Maiti)
o In Agriculture, costing left to the government creates a quasi standard instead of
providing a cut off point for minimum feature and performance. Costing is a
design issue, and manufacturers would generally contact the indentor, or a
designer to mediate in the costing between supplier and buyer.
(Mr. Swaraj Mohanti corroborated this point of view from his experience in getting a bed
raiser fabricated in the Odisha state. Finally, he got it done at Raipur, which had well
developed systems of consultation between buyer seller.)
o The design of the transaction was important. There was merit in converting
farmers and Agri Enterprises to MSME, since the MSME sector had well
developed mechanisms for buyer seller consultation (B2B and B2C), consumer
redressal, payment systems, contracting and guarantees, and property rights.
Conclusion of Day 1: to hold a Face to Face meeting with equipment manufacturers and
pricing mediators (designers) at CTTC. Overall, it can be seen that pricing conveys design
information better than any other channel. It also pools experience and information, and gets
self structured into dominant patterns. The mode of exchange also matters, such as controlled
price, mediated negotiation, direct contact or distribution systems, and derivatives pricing.
7
Creating a Hunger for High End CAE Design Tools
DAY 2: STAKEHOLDER CONSULTATION Day 2 was tilted towards Skill Building in an attempt to define the Redesign of Workstations as
the method of choice of Design Solutions in Agro Processing Industries. The effort was to
impress upon participants that most Design Solutions were formulated “out of the box”.
To actualise “out of the box”, outcome of the seminar on CAE held at CTTC was fed into the
concurrent workshops of Agro Processing Cluster and Agriculture Equipment Cluster. The
media was also involved, making the larger public a passive participant in the deliberations.
Day 2 Morning: Seminar on Point Cloud to Future Designers (Students)
Extracts of the NAS report were provided to 41 engineering students, and a workshop/seminar
was held on CAE (Computer Aided Engineering) with an exposure to Point Cloud.
Point Cloud is a well known tool used for Reverse Engineering and Redesign. There is no doubt
that Redesign is a team effort, combining Skills in mathematics, converting Point Cloud to a 3D
solid model, software programming, and Tool Post Movement and Post Processing for getting it
machined in a machining centre. (Women excel in team skills). These students were given
portions of the NAS report on Agro Processing Cluster and Agril Equipment cluster as handouts.
The outcome of Skill Building of undergraduates was that some of them set their goals for the
long haul needed to build skills in Design. This outcome along with feedback of students was
fed into the DAP workshop and the scope amplified as given below. It justified the cluster
approach to finding Design Solutions and importance of Inter Cluster Communication.
In the Classrom
8
Cluster Based Approach
A cluster is a collection of industries making similar products and located in the same Geographical region
Government promote clusters as a cost effective means of providing employment and job security
Some clusters have existed for hundreds of years, others are just emerging
If a cluster is not growing, it is dying.
Clusters sustain growth by “top up” infusion of new technologies and skills
Clusters reinvent themselves by innovations in manufacturing process
Plasma Reactor Components of this equipment was fabricated in the cluster and assembled by Saroj Meta Tech.
Cold Plasma Kills Bacteria in
Food and Beautycare
MSME CLUSTER ADOPTS “CLOUD OF POINTS” TO
MODERNISE MANUFACTURING PROCESS
Cloud of Points (Unit Operations) Covering Workstations of Agriculture Sector
Plasma is a “cloud” of electrons in a gas with temperature is thousands of degrees compared to that of gas molecules (in range of 45-2000oC). The “cloud” is contained in the Reactor and manipulated by electrical fields to give a converging gas stream exiting from a torch/nozle at high temperature to melt / join / or cut metals.
ADVANCES IN UNIT OPERATIONS
Design and Development of Paddy Transplanter in the
Cluster
Reverse Engineering Using “Point Cloud” and CAE, CAD
Dr. N. P. Gantayet, Consultant to National Institute of Design discussing Design Issues with MSME Units
9
Evening: Prof Nanda took up the refrain of Day 1, suitably modified to suit the mixed audience.
Point Cloud is a method of creating a 3D CAD model based on scanned coordinate of a
non linear surface, especially useful in Reverse Engineering and Redesign
o The method consists of fitting equations to data using an estimator like Sum of
Squares. The mathematical analysis is same as that used in Response Surface
Methodology by most students of science and engineering, quality control
engineers, Computer Aided Manufacturing and engineering optmisation.
o It is a commonly used to make inferences on experimental data, such as optimal
design of the plough that follows a family of curves y = exp (ax + b), where the
constants a and b depend on characteristic of soil
Point Cloud can be generated by a set of equations in regions where discontinuity of
mathematical functions is experienced, such as making components of die or mould
o Many parts need a change in material of construction to FRP, such as Seed Drill.
Making moulds would benefit if the surface was developed using point cloud
o Many equipments having non linear motions (inverse kinematics) can use point
cloud methodology, such as robotic applications
Use of sensors and electronic components to measure rate of flow of material like
seeds, or fertilizer, or organic material, functions as a Point Cloud generator
o Non linear surfaces having engineered friction characteristics could sort and
grade material, such as separation of broken grains of rice from whole grains
during the rice milling of basmati. Currently accomplished manually using
bamboo. (Note: jigging Unit Operations use Monte Carlo simulations and Markov
Chain analysis instead of Sum of Squares method).
In general, methods and techniques of plotting and analysing experimental data to fit a family of
equations, or a series function like Jacobian, Fourier, normal distribution, or Poisson distribution
has been adapted into manufacturing engineering. Data points of a scanned surface are used
as experimental data, i.e. a value obtained from some measuring instrument.
The other feature of point cloud is that most of the procedures of manufacturing engineering as
well as Unit Operations are done in computerised workstations. This makes it women friendly.
10
The Stakeholders of Agro Processing Design
Mr. Swaraj Mohanti, cluster organiser of Farmers, picked up the issue of pricing and price
structure of the distribution system.
Techies MSME Entrepreneurs Farmers Academy
11
Opinion on this was sharply divided, with farmers wanting higher productivity with greater extent
of mechanisation, and others from the Academy and Design Experts opting for greater Value
Addition in farm with processing.
To support greater productivity, farmers reiterated the concern for middleman taking away all
the margins of increase in prices, rising cost of labour, and unavailability of labour. Value added
activity would need skilled labour, and with labour scarcity, it would be a dicey proposition.
In support of Value Added activities, Academy and Design Experts pointed out reduction of
wastage (around 35-40%) would increase turnover and offset rising cost of labour with only
marginal investments.
Dr. Kalpana Raiguru, Guest Speaker, shared her experience of (sour) pineapple processing in
micro enterprises of Gajapati district. Shri Saroj Patnaik shared the experience of Bilati Orissa, a
Rs 20 crore investment in Agro Processing for making tomato and mango pulp suitable for
export. Both these experts supported widely distributed Agro Processing at cluster level.
CONCLUSION When a debate is not conclusive, but both argument and counter argument have sound reasons
with supporting facts and common information, it generally indicates stable asymmetry as in
summer/winter, carrot/stick, or steady state turbulent flow in churning and mixing. In general,
Agro Processing faces a lot of risks due to seasonal availability of the raw material, and great
variation in the prices of the raw material, but stable MRP (Maximum Retail Price) for the
processed product. Margins are very low for individual processors, and economies of scale
make investments prohibitively high, which acts as a barrier. Individual processors have to
invest in upstream operations like cold storage, and working capital finance for procurement and
social engineering to get cooperation from SMF (Small and Marginal Farmers).
The direction of optimal scale of operation appears to be to make it into a cluster level activity
on a lower scale of operation rather than depend on Mega investments. The advantage is risks
would even out through a portfolio of products. Clearly, grounding such activities in a cluster
would need a cross cutting game changer, such as gender sensitivity of incentive structure and
making workstations women friendly. These strategies dovetailed to Skill Building and extension
activities by Cluster Development Actors, preferably women knowledge workers with technical
skills, would be the focus of design interventions, and strategising design solutions.