materials requirements planning vs just in time

8/10/2019 materials requirements planning vs just in time

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www.izmirekonomi.edu.tr

Asst. Prof. Dr. Mahmut Ali GKE, Izmir University of Economics

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Chapter 7Push and Pull Production

Control Systems


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Basic Definitions

MRP.(Materials Requirements Planning). MRP is the basicprocess of translating a production schedule for an endproduct (MPS or Master Production Schedule) to a set ofrequirements for all of the subassemblies and parts needed

to make that item.

JIT.Just-in-Time. Derived from the original JapaneseKanban system developed at Toyota. JIT seeks to deliver theright amount of product at the right time. The goal is toreduce WIP (work-in-process) inventories to an absoluteminimum.


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Comparison

These methods offer two completely different approaches to basic

production planning in a manufacturing environment. Each hasadvantages over the other, but neither seems to be sufficient on itsown. Both have advantages and disadvantages, suggesting thatboth methods could be useful in the same organization.

Main Advantage of MRP over JIT: MRP takes forecasts for end

product demand into account. In an environment in whichsubstantial variation of sales are anticipated (and can be forecastedaccurately), MRP has a substantial advantage.

Main Advantage of JIT over MRP: JIT reduces inventories to a

minimum. In addition to saving direct inventory carrying costs, thereare substantial side benefits, such as improvement in quality andplant efficiency.


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MRP Basics

The MRP system starts with the MPS or MasterProduction Schedule. This is the forecast for the

sales of the end item over the planning horizon.

The data sources for determining the MPS

include: Firm customer orders

Forecasts of future demand by item

Safety stock requirements

Seasonal variations

Internal orders from other parts of the organization.


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Schematic of the

Productive System (Fig. 7.1)


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The Three Major ControlPhases of the Productive System (Fig. 7.2)




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The Explosion Calculus

The explosion calculus is a set of rules for converting themaster production schedule to a requirements schedule forall subassemblies, components, and raw materials necessaryto produce the end item.

There are two basic operations comprising the explosion

calculus: Time phasing. Requirements for lower level items must

be shifted backwards by the lead time required toproduce the items

Multiplication. A multiplicative factor must be applied

when more than one subassembly is required for eachhigher level item.




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The Product Structure Diagram

The product structure diagram is a graphical

representation of the relationship between

the various levels of the productive system. It

incorporates all of the information necessaryto implement the explosion calculus. Figure

7-3 (next slide) depicts an end item with two

levels of subassemblies.




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Typical Product Structure

Diagram (fig. 7-3)




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Trumpet and Subassemblies (Fig. 7-4)




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Product Structure Diagram

for Harmon Trumpet

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Explosion Calculus

Rules for translating gross requirements at one level to production

schedule at that level and requirements at lower levels.

Example

Basic Equation:Net Req. = Gross req. - Scheduled Receipts - projected on hand

inventory

Basic Algorithm

1. Compute time-phased requirements

2. Determine Planned Order Release (LS)

3. Compute ending inventory

4. Proceed to next level (if any)

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Explosion Calculus

Schedule for end item A:

Week 8 9 10 11 12 13 14 15 16 17

Gross Req 77 42 38 21 26 112 45 14 76 34

Sch Rpt 12 6 9

Inv 23Net Req 42 42 32 12 26 112 45 14 76 34

Schedule for item B (1 unit/2 weeks)

Week 6 7 8 9 10 11 12 13 14 15

Gross 42 42 32 12 26 112 45 14 76 34Schedule for item C (2 units/4 weeks)

Week 4 5 6 7 8 9 10 11 12 13

Gross 84 84 64 24 52 224 90 28 152 68

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Fall, 200715 of 28Lot Sizing For MRP Systems

The simplest lot sizing scheme for MRP systems islot-for-lot (abbreviated L4L). This means thatrequirements are met on a period by period basis asthey arise in the explosion calculus. However, more

cost effective lot sizing plans are possible. Thesewould require knowledge of the cost of setting up forproduction and the cost of holding each item. Thisbrings to mind the EOQ formula from Chapter 4,

which can be used in this context. However, thereare better methods.

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Statement of the Lot Sizing Problem

Assume there is a known set of requirements (r1,r2, . . . rn) over an n period planning horizon.Both the set up cost, K, and the holding cost, h,are given. The objective is to determineproduction quantities (y1, y2, . . ., yn) to meet therequirements at minimum cost. The feasibilitycondition to assure there are no stockouts in anyperiod is:

1 1

for .1j j

i i

i i

y r j n

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Methods

One could apply the EOQ formula by defining

but there are better methods.

Property of the optimal solution: every optimal solution orders

exact requirements: that is,

One method that utilizes this property is the Silver MealHeuristic. The method requires computing the average costfor an order horizon ofjperiods forj = 1, 2, 3,etc. and

stopping at the first instance when the average cost functionincreases. The average cost for a production quantityspanning j periods, C(j), is given by:

1

1 n

i

i

rn

1 1 1 1 2 1 1 2or ,. . ., or ... ny r y r r y r r r

2 3( ) ( 2 ... ( 1) ) /jC j K hr hr j hr j

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Methods (continued)

Another method that is popular in practice ispart periodbalancing. Here one chooses the order horizon to most closelybalance the total holding cost with the set-up cost.

Finally, a third heuristic is known as the least unit cost heuristic.Here one minimizes the average cost per unit of demand (as

opposed to the average cost per period as is done in the SilverMeal heuristic.) The average cost per unit of demand over jperiods is given by:

2 3 1 2( ) ( 2 ... ( 1) ) /( ... ).j jC j K hr hr j hr r r r

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Methods (concluded)

Experimental evidence seems to favor theSilver Meal Heuristic among the fourdiscussed as the most cost efficient.

Optimal lot sizes can be found by usingbackwards dynamic programming.

A heuristic method for lot sizing subject tocapacity constraints is discussed in this

section.

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Fall, 200720 of 28Shortcomings of MRP

Uncertainty. MRP ignores demand uncertainty, supply uncertainty,and internal uncertainties that arise in the manufacturing process.

Capacity Planning. Basic MRP does not take capacity constraintsinto account.

Rolling Horizons. MRP is treated as a static system with a fixedhorizon of n periods. The choice of n is arbitrary and can affect theresults.

Lead Times Dependent on Lot Sizes. In MRP lead times areassumed fixed, but they clearly depend on the size of the lotrequired.

Quality Problems. Defective items can destroy the linking of thelevels in an MRP system.

Data Integrity. Real MRP systems are big (perhaps more than 20levels deep) and the integrity of the data can be a serious problem.

Order Pegging. A single component may be used in multiple end

items, and each lot must then be pegged to the appropriate item.

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Introduction to JIT

JIT (Just In Time) is an outgrowth of the Kanban systemdeveloped by Toyota.

Kanban refers to the posting board where the evolution of themanufacturing process would be recorded.

The Kanban system is a manual information system thatrelies on various types of cards.

Its development is closely tied to the development of SMED:Single Minute Exchange of Dies, that allowed modelchangeovers to take place in minutes rather than hours.

(The mechanics of a typical Kanban system are pictured inFigure 7-8.)

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Kanban System for Two Production

Centers (Fig. 7-8)

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Features of JIT Systems

Small Work-in-Process Inventories.

Advantages:

1. Decreases Inventory Costs

2. Improves Production Efficiency3. Reveals quality problems (see Figure 7-10)

Disadvantages:

1. May result in increased worker idle time

2. May result in decreased throughput rate

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River/Inventory AnalogyIllustrating the Advantages of Just-in-Time

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Features of JIT Systems (continued)

Kanban Information Flow System

Advantages:

1. Efficient tracking of lots

2. Inexpensive implementation of JIT

3. Achieves desired level of WIP

Disadvantages:

1. Slow to react to changes in demand

2. Ignores predicted demand patterns

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Kanban Information System vs

Centralized Information System (MRP)


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i i k i d t


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Comparison of MRP and JIT

Major study comparing MRP and JIT inpractice reveals:

JIT works best in favorable manufacturingenvironments: little demand variability, reliablevendors, and small set up times

MRP (and ROP based on Chapter 5 methods)worked well in favorable environments (comparableto JIT) and better in unfavorable environments.

materials requirements planning vs just in time

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