Push vs. Pull Process Control

Push vs. Pull Process Control

IE 3265 POM

Slide Set 9

R. Lindeke, Sp 2005

Basic Definitions

MRP (Materials Requirements Planning). MRP is the basic process of translating a production schedule for an end product (MPS or Master Production Schedule) to a set of time based requirements for all of the subassemblies and parts needed to make that set of finished goods.

JIT Just-in-Time. Derived from the original Japanese Kanban system developed at Toyota. JIT seeks to deliver the right amount of product at the right time. The goal is to reduce WIP (work-in-process) inventories to an absolute minimum.

Why Push and Pull?

MRP is the classic push system. The MRP system computes production schedules for all levels based on forecasts of sales of end items. Once produced, subassemblies are pushed to next level whether needed or not.

JIT is the classic pull system. The basic mechanism is that production at one level only happens when initiated by a request at the higher level. That is, units are pulled through the system by request.

Comparison

These methods offer two completely different approaches to basic production planning in a manufacturing environment. Each has advantages over the other, but neither seems to be sufficient on its own. Both have advantages and disadvantages, suggesting that both 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 which substantial variation of sales are anticipated (and can be forecasted accurately), 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, there are substantial side benefits, such as improvement in quality and plant efficiency.

Comparisons (cont.)

Advantages Disadvantages

JIT PULL

Limited and known Final InventoryEvery job is a ‘High Stress’ Rush order

Worker only consume their time & Raw Materials on what is actually needed

Balanced systems MUST be in place

Quality MUST be High – each piece has a definite place to go – else immediate feedback is given

Setup times will greatly impact throughput

Any problem will lead to unhappy customers (either internal or external)

Comparisons (cont.)

Advantages Disadvantages

MRP PUSH

Allows Managers to manage – that is, plan and control things

Can lead to large inventories

Requires intricate knowledge of Production Times & Product Flow

Can generate large quantities of scrap before errors are discovered

Can lead to economies of scale in purchasing and production

Requires diligence to maintain effective product flow

Allows for the planning and completion of complex assemblies as sub-components are delivered only by scheduled need

Requires maintenance of large and complex databases

Focusing on JIT

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

Kanban refers to the posting board (and the inventory control cards posted there) where the evolution of the manufacturing process would be recorded.

The Kanban system is a manual information system that relies on various types of inventory control cards.

It’s development is closely tied to the development of SMED: Single Minute Exchange of Dies, that allowed model changeovers to take place in minutes rather than hours.

The Fundamental Idea of JIT – and Lean Manufacturing Systems in General (an Americanization of the Toyota P. S.) – is to empower the workers to make decisions and eliminate waste wherever it is found

The Tenets of JIT/Lean

Empower the workers: Workers are our intelligent resources – allow them to

exhibit this strength Workers ultimately control quality lets them do their job

correctly (Poka-Yoke) Don’t pit workers against each other – eliminate “piece-

work” disconnected from quality and allow workers to cooperate in teams to design jobs and expectations

The Tenets of JIT/Lean

Eliminate Waste– Waste is anything that takes away from the operations

GOAL (to make a profit and stay in business!) Reduce inventory to only what is absolutely needed Improve Quality – scrap and rework are costly and disrupt flow Only make what is ordered Make setups and changes quickly and efficiently Employ only the workers needed Eliminate Clutter – it wastes time

Features of JIT Systems

Small Work-in-Process Inventories.

Advantages:1. Decreases Inventory Costs2. Improves Efficiency3. Reveals quality problems (see Figure 7-10)

Disadvantages:

1. May result in increased worker idle time2. May result in decreased throughput rate

River/Inventory Analogy Illustrating the Advantages of Just-in-Time

Revealing fundamental ‘problems’ is the noted competitive advantages of JIT/Lean

Features of JIT Systems (continued)

Kanban Information Flow System Advantages1. Efficient tracking of lots2. Inexpensive implementation of JIT3. Achieves desired level of WIP – based on Number of

Kanbans in the system

Disadvantages1. Slow to react to changes in demand2. Ignores predicted demand patterns (beyond 2 months or so)

Focus on The Kanban

Typically it is a 2-card system The P (production) Card and W (withdrawal) Card Limits on product inventory (number of P & W cards)

are set by management policy The count is gradually lowered until problems

surface The actual target level (card count) is based on short

term forecasting of demands

Focus on The Kanban

Focus on The Kanban – the worker as manager

P cards cycle from their accumulation post at Center 1 to product (when a defined trigger point is reached) and then to output queue

When trigger level is reached, Ct 1 worker pulls product from Ct 1 Wait point queue and replaces the Ct 1 W-cards with Ct 1 P-Cards which then are loaded to the Ct 1 processors – the worker puts Ct 1 W-Cards to his/her acc. Post for W-cards

Finished Product is pushed into the Ct 1 output queue

Focus on The Kanban – the worker as manager

A second worker (Ct 2’s worker) watches for accumulation of Ct 2 W-Cards

When it reaches their trigger level, he/she pulls product into Ct 2 Holding area after replacing Ct 1 P-Cards with their W-Cards – and returns Ct 1 P-Cards to their Acc. Post for Ct. 1 workers benefit

They also watch for accumulation of Ct. 2 P-Cards on their acc. Post and when trigger count is reached they pull product from holding area and replace Ct 2 W-Cards w/ Ct 2 P-Cards then push it into the processors

And around and around they go!

Focus on The Kanban

So how many cards? – speaking of which, a card is associated with a container (lot) of product so the number of P & W cards at a station determines the inventory level of a product!

is # of Kanbans

D is 'average' demand

L is lead time (proc+wait+travel+others)

w is buffer stock/ set by policy

typically 10% of DL

a is container cap. < 10% of daily demand

DL wy

ay

Focus on The Kanban

Lets look at an example: 950 units/month (20 productive days) → 48/day Container size: a = 48/10 = 4.8 → 5 “L” data:

– A. setup is 45 minutes (.75 hour)– B. Setup is 3 minutes (.05 hr)– Wait time: .3 hr/container– Transport time: .45 hr/container– Prod Time: 0.09 hr/each = .45 hr/container

Focus on The Kanban

.45 .75 .3 .45 1.95

48/8 6 /

6 1.95 11.7; .1 11.7 1.17

11.7 1.172.57 3

5

a

a a

a

L hr

D hr

DL w

y

.45 .05 .3 .45 1.25

6 1.25 7.5

.1 7.5 .75

7.5 .751.65 2

5

b

b

b

b

L hr

DL

w

y

Requires 3*2 = 6*5 = 30 pieces in inventory – also, with 45mins set up 10 times a day means that we consume 450 min or 7.5 hours/day just setting up!

Here only 2*2 = 4*5 = 20 pieces and also only .05*10 = 50 min for setup (.833 hr) per day

So, setup reduction impacts Factory Capabilities & Inventory

Lets look at the effect of studies comparing cost of setup vs. inventory cost – like EOQ

Then lets see what we can invest to reduce inventory levels

We will spend money on reducing setup cost (time) and see if reduced inventory will offset our investment

This is the driving force for SMED

,2

Like in EOQ

but last term is a 'Penalty'

factor for investing in setup

reduction rather than other

projects

K hQG Q K I a K

Q

Focus on the Penalty Factor

We can effectively model this “a(K)” function as a ‘logarithmic’ investment function

By logarithmic we imply that there is a an increasing cost to continue to reduce setup cost

We state, then, that there is a sum of money that can be invested to yield a fixed percentage of cost reduction

That is (for example) for every investment of $200 the organization can get a 2% reduction in Setup cost


Lets say that the investment is $ buys a fixed percent reduction in K0

If we get actually get 10% setup cost reduction for $, then an investment of $ will mean:

– Setup cost drops to: 0.9K0

A second $ investment will lead to a further 10% reduction or:

– .9K-.1*.9K = .81K0

This continues: K3 = .729K0

Generalizing:

0

is 'number' of investments

q is the decimal equivalent of the

amount of reduction the $

investment will buy:

q=(1-%setup cost reduction)

ja q K j

j


With that “shape” we can remodel the a(K) logarithmically:

a(K) = b[ln(K0) – ln(K)] where:

Reverting back to G(Q,K) function – and substituting Q*:

1lnb

q

02 ln( ) ln

now, minimize w.r.t. K

meaning: G'(K) = 0

G K K h I b K K


Finding the K* after the minimization:

To determine what we should do, determine G(K) using K0 and K*

2 22

I is MARR for the company

I bK

h

Lets try one:

K0: $1000 : $95 for each 7.5% reduction in setup cost Annual quantity: 48000 Holding cost: $4.50 MARR is 13%

2 2

95 951218.55

.077961ln1 .075

2 .13 1218.55$0.232

48000 4.5

b

K

Continuing:

Investment to get to K*

Testing for decision

No investment (K = K0):

At Min K*:

1218.55 ln 1000 ln .232

$10195.91

a K

0 0

0

2 $20784.61

2: 4619

G K K h

Knote EOQ piecesh

2

316.58 1325.47 $1642

2 70

G K K h Ia K

KEOQ K h

SMED

Some terms:

SMED = single minute exchange of dies which means quick tooling change and low setup time (cost)

Inside Processes setup functions that must be done ‘inside’ the machine or done when the machine is stopped

Minimally these would include unbolting departing fixtures/dies and positioning and bolting new fixture/dies to the machine

More Terms:

Outside Setup activities related to tooling changes that can be done ‘outside’ of the machine structure– These would include:

Bringing Tooling to Machine Bringing Raw Materials to Machine Getting Prints/QC tools to machine Etc.

Focus on SMED

When moving from “No Plan” or Step 1 to Step 2 (separating Inside from Outside activities) investments would be relatively low to accomplish a large amount of time (cost) saving– Essentially a new set of change plans and a small

amount of training to the Material Handlers so that they are alerted ahead of time and bring the tooling out to the machine before it is needed

Moving to Step 3 and Step 4

Require investments in Tooling Require Design Changes Require Family tooling and adaptors Require common bolstering attachments In general requiring larger and larger

investments in hardware to achieve smaller and smaller time (cost) savings in setup

Therefore, we can say SMED is:

In reality the essence of a Logarithmic setup reduction plan!

Lets Look into Line Balancing

This is a process to optimize the assignment of individual tasks in a process based on a planed throughput of a manufacturing system

– It begins with the calculation of a system “Takt” or Cycle time to build the required number of units required over time

– From takt time and a structured sequential analysis of the time and steps required to manufacture (assembly) a product, compute the number of stations required on the line

– Once station count is determined, assign feasible tasks to stations one-at-a-time filling up to takt time for each station using rational decision/assignment rules

Line Balancing

Feasible tasks are ones that have all predecessors completed (or no predecessors) and take less time that the remaining time at a station

Feasibility is also subject to physical constraints:

Zone Restriction – the task are physically separated taking to much movement time to accomplish both within cycle (like attaching tires to front/back axles on a bus!)

Incompatible tasks – the Grinding/Gluing constraint

Some of the Calculations:

Takt (Cycle) Time:

Minimum # Workstations req’r:

Prod. time/day Total Time - Allowances (T)

Target output/day Req'r Output (Q)

(min/unit)

C

TC Q

(Total Job Task Time)tN C

Efficiency Calculations:

1

1

i

j

here t is the time actually consummed at the stations

t is the time of any task actually assigned to St K

N

ii

line

J

jj

StK

i tEff

C N

t

EffC

Lets Try One:

A B C

D E F

G H

Times:

A 25s; B 33s;C 33s; D 21s; E 40s; F40s;

G 44s; H 19s

Production Requirement is 400/shift

Calculation of Takt Time & Optimal Station count

480 .12* 480 422.41.056min 63.4

400 400C s

25 33 33 21 40 40 44 194.04

63.45

itNC

N stations

To Perform Assignment we need Assignment Rules:

Primary Rule: – Assign task by order of those having largest

number of followers

Secondary Rule: – Assign by longest task time

Primary Assignment Rule

Task # Followers

A,D 4

E,B 3

F,C 2

G 1

Line Balancing Assignments

Station Task T. TimeRemaining Time

Feas. Remaining Task

Task w/ Most followers

Task w/ L. Time

1A 25 38.4 B, D D B

D 21 17.4 -

2 E 40 23.4 -

3 B 33 30.4 -

4 F 40 23.4 -

5 C 33 30.4 -

6G 44 19.4 H

H 19 .4 -

The Line Balance

A B C

D E F

G HWS 1

WS 3

WS 2 WS 4

WS 5

WS 6

Checking Efficiencies:

1

3

6

25567%

6 63.446

72.6%63.433

52.1%63.463

99%63.4

L

S

S

S

TEff

C N

Eff

Eff

Eff

Dealing with Efficiencies

We investigate other Rules – application to improve layout

1st by followers then by longest time then most followers Alternating!

Consider line duplication (if not too expensive!) which lowers demand on a line and increases Takt time

The problem of a long individual task In Koeln, long time stations were duplicated – then the system

automatically alternated assignment between these stations

Documents

Push vs. Pull Process Control