specific management tools and her practical suitability ... management tools and her practical...
TRANSCRIPT
Specific management tools and her practical suitability for the beverage industry
Dipl.-Ing. Michael M. Braitinger, Business Management and Economics, Faculty of Business and Economics, Mendel University in Brno,
Abstract
The beverage industry in Europe is characterized by mass production. To produce beverages
complex technical systems are necessary. These systems are capital intensive, both in
investment and in the production phase.
The refinancing of such investments must be seen against the background of a little
growing sales and the behavior of a polypolistic market for beverages.
These investments are more combinations of labor rationalizations together with
technological improvements, there are now less capacity expansions in consideration as it was
during the last decades. These investments alone are no guarantee for economic success.
Optimal use could be achieved only through the permanent application of management tools.
The goal of these tools is to avoid losses, increasing availability of production and the
improvement of the overall equipment effectiveness (OEE).
As a part of this study the possibilities of certain tools are also shown.
In an empirical long-term observation project (from 2008 – 2012), the Overall
Equipment Effectiveness (so called OEE) of two bottling plants in the beverage industry have
been studied. The studies took over 5 years and have been carried out based on the calculation
methodology for OEE as a management tool. In addition to this, the empirically collected data
were processed with the German “DIN 8782”, to highlight the suitability of this method for
this project. In this paper, the shape of the data analysis and the results thus obtained is
shown.
Key Words
Bottling line utilization, Overall equipment effectiveness, DIN 8782, long term production
monitoring.
Introduction
Production and sale of beverages in Germany take place in a polypolistic market. The
beverage industry is characterized by mass production. Until about 1990 drinks were bottled
in glass or metal containers, such as cans or kegs, or barrels of beer.
The introduction of PET bottles instead of glass bottles as packaging for soft drinks in Europe
has changed the beverage market sustainable. These changes affect both the logistics and
production engineering. In connection with the introduction of the PET bottle substantial
investment in bottling and packaging PET bottles are made. The investments in these PET
bottling lines were capital intensive.
With reference to the circumstances of a polypolistic market system, this development also
brought up significant disadvantages for low capitalized firms in polypolistic market events.
Such disadvantages were a lack of attractiveness of the product and its packaging, high
logistics costs compared to PET goods handling and the still remaining various risks from the
material Glass.
It was observed that due to the capital required for the acquisition of such filling, competitive
pressures within the producers increased.
Here arises a typical dilemma of the beverage industry:
On the one hand, the plants have to run as long as possible without interruption to achieve a
profitable asset utilization, on the other hand, the systems need to be flexible to respond
quickly to market demands, such as small batch or special packaging.
In addition, it should be noted that the beverage manufacturers have the choice between two
technologically different filling systems. Both systems have different investment financing
needs. This leads to different overheads in product pricing. This advantage or disadvantage
surfaced only after the end of the amortization period.
The author carried out a long-term empirical study of the Overall Equipment Effectiveness1
(OEE)2 for these technological different filling lines.
All results of this long-term monitoring are the subject of a thesis of the author.
The filling lines – as shown in Fig. 1 - have basically a similar technical layout. Both filling
and packaging plants produce Icetea in PET bottles, 6 bottles each with a capacity of 1.5 liters
as packaging unit.
The filling process itself was technologically different. The difference in the technology is the
type of the product preservation during bottling.
In the Cold aseptic filling line filling (CAF) the packaging (bottle), the product and the
closures are made germ-free through physical methods (pasteurizing effects).
In the cold sterile filling line filling (CSF) the product will be sanitized using a specific
chemically method3 through microbiological oxidation effects.
1 NAKAJIMA, S., Introduction to TPM, USA, Productivity Press Cambridge
Massachusetts, 1988, pp 27, ISBN 915299232 2 May, Constantin, Koch, Arno (2008), Overall Equipment Effectiveness (OEE) – Tool
to improve productivity (Werkzeug zur Produktivitätssteigerung), Journal of Consulting
(Zeitschrift für Unternehmensberatung) Vol 06/08, pp.245-250, Erich Schmidt Press,
Berlin, ISSN 1863-3889 3 The method relies on the use of Dimethyldicarbonate. It is marketed under the trade
name Velcorin ® from Lanxess AG. Dimethyldicarbonate is approved as a food
additive number E 242 and as free of declarable for 'cold sterilization' processes under §
(Source: own)
Figure 1 Bottling process mapping
Objectives and methodology
As part of a long-term empirical observation, it was necessary to find a methodological
approach to data collection and processing. The collection of primary data had to be done by
the operator.
After manual plausibility control, a simple algorithm to process the data should be available.
The objective of the data processing will be statements concerning the productivity and
utilization of the examined time filling equipment.
In the beverage industry, different Management tools are used for analyzing production
situation and economy. Some of these management tools are listed below:
5 (COMMISSION REGULATION (EC) No 2165/2005 of 20 December 2005
amending Regulation (EC) No 1493/1999 on the common organization of the wine.) of
the additive approval regulations for non-alcoholic flavored drinks, wine, non-alcoholic
wine and Liquids
Stretch blow
molding Machine
Stretch blow
molding Machine
Air conveying
system
Air conveying
system
Cold Aseptic
Filling bloc
with rinsing
filling and
closing.
Cold SterilizationFilling bloc
with rinsing
filling and
closing.
PET preformsPET preforms
Closures, product
and bottle
sterilization
unit
Beverage
mixer
Supply: water, ingredients, sugar, flavours etc.
Auxiliaries units: Electric and thermal power,compressed air supply, process gas media (CO2,
N2), process supporting chemicals, et alt.
Beverage
mixer
Human Resources
Labelling Labelling
Multipack
systems
Multipack
systems
Palletizer Palletizer
Stretch Wrapper Stretch Wrapper
Warehouse
Supply
Bottling
Distribution
Technical
additives
Table 1 : Management tools
Source: Evers, H., Berlin (11/2013), „Overall Equipment Effectiveness or the famous DIN
8782 - Comparison of key factors in the value chain” Presentation at the 13th Congress of the
International Fresenius "Sensitive Beverages
Table 2 : Management tools
Source: Evers, 2013
Research aerea Management tool
To high production costs OEE, OAE; GAE
to low plant productivity OEE = Overall Equipment Effectiveness
Too low operational productivity OAE = Overall Asset Efficiency
Lack of transparency of machine losses GAE = Gesamtanlageneffektivität
Lack of transparency in the capacity calculation
Frequent deviations from the plan (contract duration /
contract term
Excessive stocks Kanban
High inventory costs Kanban = Analysis Pull / Pull Principles
Long lead times
Excessive stocks QCO, SMED
to high capacity losses due to conversions QCO = Quick Change over
Increasing variety and lack of capacity SMED = Single Minute Exchange of Die
unclear situation Value Stream Map
Inadequate definitions in the KVP Process
to high production costs
Quotas of returning goods
lack of capacity
Lack of order and cleanliness 5 S / 5 A / Muda
High productive time for searching and waiting
Nervous tension of personnel due to chaos in the
production
Recurring error
to high error rate Poka Yoke
Increasing number of customer complaints System to identify and avoid technical
Low quality rate mistake - key-lock-principle
High quality costs
Rarely flawless runs of processes
Recurring error
Too little change dynamics KVP / Six Sigma
Insufficient implemented improvements Six Sigma in combination with DMAIC =
Little motivated employees Define - Measure - Analyze - Improve -
Interface problems (example: production-> Planning,
production-> Logistics) Control
No KVP / Kaizen culture available
For long-term observation study on the availability of the filling lines the OEE method was
used with the internationally accepted accounting framework4.
Source: DIN 8782, (May 1984) Definitions for bottling lines and single components
Figure 2: Method of calculating DIN 8782
4 NAKAJIMA, S., Introduction to TPM, USA, Productivity Press Cambridge Massachusetts, 1988, pp 27,
ISBN 915299232
Working time (Definition Nr. 3.7 and 3.4 at DIN 8782)
Operating time
(Working time - sheduled shutdown time)
(Definition Nr. 3.5 and 3.4 at DIN 8782)
Net operating time
(Operating time - time for external
caused stoppages) (Definition at 3.3
-> DIN 8782)
effective operating time
(Definition Nr. 3.1 ->
DIN 8782)
Minus sheduled downtime time:
Process support time and tool
change (i.e change of packaging)
or startup of the process
Minus external caused stoppage times:
Operator failure, no supply of process
materials incl. power breakdown
Minus internal caused stoppage times:
technical defects in the line causing stopps or reduced
line speed
DIN 8782 timeline for beverage filling
Parameters for bottling lines acc. DIN 8782
Nominal output line in Bph or similar = QnA = produced goods ÷ time unit
Effective Output in Bph or similar = Qeff A = produced goods ÷ net operating time
Average Output in Bph or similar = Q m A = produced goods ÷ working time
Line utilisation % = φ A = Average Output ÷ Nominal Output ( Qeff A ÷ QnA)
Source: May, Koch, 2008
Figure 3 : Method of calculating OEE
Both methods - OEE5 and DIN 8782 - refer to the relation of production volumina and
operating times.
Data collection by the operator of the filling lines was restricted to a minimum.
Per calendar week following data had to be entered in a record sheet:
Scheduled Downtime
Downtime caused by external factors
Downtime Caused by line internal factors
Net operating time
Filling amount in bottles
Filling amount in hectoliters
5 NAKAJIMA, S., Introduction to TPM, USA, Productivity Press Cambridge Massachusetts, 1988, pp 27,
ISBN 915299232
Gross available time (24 hours / 7 days) The measured asset was purchased, installed and is
available for 24 hours, 7 days, all year
effective operating time
Available Output
effective Output
Minus
performance
losses:
reduced Speed,
short stoppage
correct
units
OEE Overall Equipment Effectiveness
avai
lab
ilit
y Gross available production time
No production
sheduled
Minus planned or sheduled
shutdown losses: failure, start-
up, set-up / adjust, tool
change, external limitations
A
B
C
Dper
form
ance
effective Output
Minus
defective
units
Qu
alit
y
F
E
Efficiency loosses
OEE % = Availability % x Performance % x Quality %
= (B ÷ A) x ( D ÷ C) x (F ÷ E) in %
With this information it is possible to meet the requirements for the processing of the data
material gained through the long-term observation for both the OEE and for the DIN 8782 as
seen in Tab. 3 and 4.
Table 3: Data processing scheme for the DIN 8782
Source: own
Table 4: Data processing scheme for OEE
Source: own
Results
This study is part of a long-term empirical observation on plant availability and describes the
methodology for recording and analyzing of these collected long-term data.
Modus operandi Calculation scheme for DIN 8782 units
A Working time hours per week
./. B Sheduled down time hours per week
= C Operating time hours per week
. /. D External down times hours per week
= E Net operating time hours per week
./. F internal failure time hours per week
= G effective operating time hours per week
H Nominal Outout in Bph Bottles per hour
I Produceed correct Goods Bottles per week
J = I ./. E Q eff a effective output in Bph Bottles per hour
K = I ./. A QmA average output in Bph Bottles per hour
L = K ./. H φ A line utilization in %
Calculation for OEE
A gross available production time
./. Aux. (sheduled shutdown times)
./. EFT (external limitations)
B effective operating time hours
Nominal Output line bottles per hour
C available Output bottles
./. IFT (short stoppage etc.) hours
D effective Output in h hours
E effective output in bottles bottles
F correct produced goods bottles
G OEE in % = (B ÷ A) x (D ÷ C) x (F ÷ E)
With the described methodology of data collection, it was possible to process these data
through application of the OEE and DIN 8782 model.
Different interpretations of the numerical values found are possible. But at one point, both
methods yield the same conclusion, namely, "OEE" and "Line utilization".
The study has a high proportion of manual data collection. Over the long term data entry
errors or inaccuracies evaluation by the operator were observed.
In order to avoid such errors in the future, Voigt6 reported from the results of the undergoing
project for the application of the OEE structure into a model for automated reporting systems
through the bottle filling process. This project inside the Technical University of Munich
researches how the application of the OEE supports improvements of the line availability
through the analysis of the data from the OEE point of view. Focuses on this research project
are among others the improvement of maintenance, reduction of casual failure times through
continuous line monitoring, reduction of defective goods.
The results of long-term observation point to differences between the systems. Based on the
obtained results, the OEE approach proves to be suitable for long-term observations and can
be performed by its simple calculation of structures also by the workers at the plant. For the
Management are the obtained results been useful as productivity indicators.
Table 5: OEE longterm results by filling line CSF
Source: own
6 Voight, T, (2011), Improvements of efficiency for bottling and packaging lines (Effizienzsteigerung bei
Abfüll- und Verpackungsanlagen), Chair of food packaging Technical university Munich, published at
“Der Weihenstephaner”, Nr. 1 (2011), p 24, Hans Carl Press, ISSN 0171-5089.
Definition 2008 2009 2010 2011 2012
A gross available production time in h 4.845,29 5.623,44 5.835,59 2.520,04 4.949,00
B effective operating time in h 4.304,39 5.022,38 5.188,14 2.191,67 4.073,93
C Available Output in bottles 90.392.190 105.469.980 108.950.940 46.025.070 85.552.530
D effective Output 85.387.050 97.761.930 100.858.800 36.099.840 85.081.080
E effective Output 85.387.050 97.761.930 100.858.800 36.099.840 85.081.080
F correct goods 67.740.990 82.753.118 85.407.814 34.754.443 65.435.496
G Nominal Outout in Bph 21.000 21.000 21.000 21.000 21.000
H Availability in % 88,84% 89,31% 88,91% 86,97% 82,32%
I Performance in % 94,46% 92,69% 92,57% 78,44% 99,45%
J Quality in % 79,33% 84,65% 84,68% 96,27% 76,91%
K OEE p.a in % 66,58% 70,07% 69,69% 65,67% 62,96%
OEE Overview for CSF
Table 6: DIN 8782 longterm results by filling line CSF
Source: own
Table 7: OEE longterm results by filling line CAF
Source: own
Table 8: DIN 8782 results by filling line CAF
Source: own
Definition 2008 2009 2010 2011 2012
A Working time 4.845,29 5.623,44 5.835,59 2.520,04 4.949,00
B Sheduled down time 513,91 584,73 609,94 301,98 829,20
C Operating time 4.331,38 5.038,71 5.225,65 2.218,06 4.119,80
D External down times 26,99 16,33 37,51 26,39 45,87
E Common operating time 4.304,39 5.022,38 5.188,14 2.191,67 4.073,93
F internal failure time 238,34 367,05 385,34 472,63 1.168,61
G effective operating time 4.066,05 4.655,33 4.802,80 1.719,04 2.905,32
H Nominal Outout in Bph 21.000 21.000 21.000 21.000 21.000
I Produced correct goods 2010 67.740.990 82.753.118 85.407.814 34.754.443 65.435.496
J Q eff a effective output in Bph 15.738 16.477 16.462 15.858 16.062
K Q mA average output in Bph 13.981 14.716 14.636 13.791 13.222
L φ A line utilization p.a in % 66,58% 70,07% 69,69% 65,67% 62,96%
The DIN 8782 Overview for CSF
Defintion 2008 2009 2010 2011 2012
A gross available production time in h 6.096,16 5.848,85 5.091,09 5.279,68 5.240,92
B effective operating time in h 3.914,86 3.779,35 3.389,01 3.504,64 3.554,10
C Available Output in bottles 93.956.640 90.704.400 81.336.240 84.111.360 85.298.400
D effective Output 62.362.560 58.386.480 52.937.760 81.506.880 83.741.520
E effective Output 62.362.560 58.386.480 52.937.760 81.506.880 83.741.520
F correct goods 59.016.570 57.964.890 51.549.594 59.819.910 61.960.032
G Nominal Outout in Bph 24.000 24.000 24.000 24.000 24.000
H Availability in % 64,22% 64,62% 66,57% 66,38% 67,81%
I Performance in % 66,37% 64,37% 65,09% 96,90% 98,17%
J Quality in % 94,63% 99,28% 97,38% 73,39% 73,99%
K OEE p.a in % 40,34% 41,29% 42,19% 47,21% 49,26%
OEE Overview for CAF
Definition 2008 2009 2010 2011 2012
A Working time 6.096,16 5.848,85 5.091,09 5.279,68 5.240,92
B Sheduled down time 2.083,06 1.866,75 1.584,25 1.666,52 1.621,95
C Operating time 4.013,10 3.982,10 3.506,84 3.613,16 3.618,97
D External down times 98,24 202,75 117,83 108,52 64,87
E Common operating time 3.914,86 3.779,35 3.389,01 3.504,64 3.554,10
F internal failure time 1.316,42 1.346,58 1.183,27 970,70 972,39
G effective operating time 2.598,44 2.432,77 2.205,74 2.533,94 2.581,71
H Nominal Outout in Bph 24.000 24.000 24.000 24.000 24.000
I Produced correct goods 2010 59.016.570 57.964.890 51.549.594 59.819.910 61.960.032
J Q eff a effective output in Bph 15.075 15.337 15.211 17.069 17.433
K Q mA average output in Bph 9.681 9.910 10.125 11.330 11.822
L φ A line utilization p.a in % 40,34% 41,29% 42,19% 47,21% 49,26%
The DIN 8782 Overview for CAF
Table 9: Results Concentrate of the long-term observation
Source: own
Source: own
Figure 4 : Long-term course of OEE and DIN 8782
The results show that the investigated filling line CSF is distinctly higher in the availability
and performance, but is inferior in quality factor of the bottling line ACF. In the course of five
years observing a trend towards improvement in productivity of the line ACF can be seen. In
contrast, a reduction in productivity can be seen in CSF system.
OEE / DIN 8782 Considerations 2008 2009 2010 2011 2012 Ø
for CSF p.a in % 66,58% 70,07% 69,69% 65,67% 62,96% 66,89%
for CAF p.a in % 40,34% 41,29% 42,19% 47,21% 49,26% 43,79%
Availability 2008 2009 2010 2011 2012 Ø
CSF 88,84% 89,31% 88,91% 86,97% 82,32% 87,19%
CAF 64,22% 64,62% 66,57% 66,38% 67,81% 65,89%
Performance 2008 2009 2010 2011 2012 Ø
CSF 94,46% 92,69% 92,57% 78,44% 99,45% 90,94%
CAF 66,37% 64,37% 65,09% 96,90% 98,17% 75,22%
Quality 2008 2009 2010 2011 2012 Ø
CSF 79,33% 84,65% 84,68% 96,27% 76,91% 83,87%
CAF 94,63% 99,28% 97,38% 73,39% 73,99% 86,13%
0,00%
10,00%
20,00%
30,00%
40,00%
50,00%
60,00%
70,00%
80,00%
2008 2009 2010 2011 2012
Uti
liza
tio
n i
n %
Year
Overview OEE or DIN 8782-> 2008 - 20121
for CSF p.a in % for CAF p.a in %
Discussion
Management decisions are often characterized by time and market pressure. Long term
planning for distribution in the beverage industry sometimes suffers due the dynamic of this
market. The influences of the weather conditions as well as the possibility of quick responses
against competition are imponderables for the production planning as well as the reliability of
the technical equipment. Consequently the focus of the management will be the choice for
bottling lines which high efficiency and defined cost structures.
Once a decision made for one or the other filling line system it can´t be revised without
further notice. And it can lead to economic losses due to calculation deficits. In polypolistic
market often determines the trade, what price the company can get its products. To avoid the
risk of losses to more expensive productions, the effectiveness of the operation must be kept
permanently high. For this purpose, the OEE supply a significant contribution method in the
context of Total Productive Maintenance with its visualization of productivity. OEE results
should be considered a starting point for further analysis in the field of Total Plant
Productivity. While OEE results have three areas namely availability, performance and
quality in focus, the productivity of evaluation according to DIN 8782 is only one of many
representations results.
Conclusion
With the indicated long-term observation of performance, availability and quality of two
bottling lines, it is also possible to observe positive or negative trends and react accordingly
based on the results found. OEE results should be considered a starting point for further
analysis in the field of Total Plant Productivity. The OEE method is used in many industries,
but only sporadically in the beverage industry, since productivity was either held by the
occasional application of DIN 8782 or their own rating systems. Even better, if as is common
in the automotive industry, the data at different locations would be anonymous collected in a
central database. With the Access for decision-makers they could experience their intentions,
weight their investments and act differently so also in the sense of sustainable finance capital.
References
EVERS, H., 2013: Overall Equipment Effectiveness or the famous DIN 8782 - Comparison
of key factors in the value chain, Paper presentation at the 13th Congress of the International
Fresenius "Sensitive Beverages" at Berlin
MAY, C., KOCH, A., 2008: Overall Equipment Effectiveness (OEE) – Werkzeug zur
Produktivitätssteigerung, Zeitschrift für Unternehmensberatung Vol 06/08, pp.245-250, Erich
Schmidt Press, Berlin, ISSN 1863-3889
DIN 8782, 1984: Begriffe für Abfüllanlagen und einzelne Aggregate, Standardization
Comitee Mechanical Engineering at the German Institute for Standardisation, Beuth Verlag
GmbH, Berlin, ISSN 0722-2912
NAKAJIMA, S., 1988: Introduction to TPM, USA, Productivity Press Cambridge
Massachusetts, 1988, pp 27, ISBN 915299232
VOIGHT, T, 2011: Effizienzsteigerung bei Abfüll- und Verpackungsanlagen, Chair of food
packaging Technical University Munich, published at “Der Weihenstephaner”, Nr. 1 (2011),
p 24, Hans Carl Press, ISSN 0171-5089.