Drum BufferRope Skorkovsk Based on R Holt Ph
Drum –Buffer-Rope Skorkovský Based on : R. Holt, Ph. D. , PE
Traditional Approach: Divide and Conquer Division of Labor breaks down linkages complex systems into manageable chunks. Which is harder to manage? Left or Right? Left Right
We Measure Operational Efficiency Work flows from left to right through processes with capacity shown. Process A B C D E FG RM Capability Parts per Day Market Request 11 7 9 5 8 6 Too Much Overtime Chronic Complainer Excellent Efficiency--Near 100%
Reward Based on Efficiency Work flows from left to right. Process A B C D E FG RM Capability P/D 7 9 5 8 Both found ways to look busy and appear to have a capacity of 5 parts/day. 6
In reality. . . Processes A and B won’t produce more than Process C for long. Process A B C D E FG RM Potential P/D 7 9 5 8 6 Reality 5 5 5
Then Variability Sets In Processing times are just AVERAGE Estimates Process A B C D E FG RM Reality 5± 2 7+9+5+8+6=35, 7=35/5=7 (average) 5± 2
What’s an Average? 50% Half the time there are 5 or more per day at each process--Half the time less Process A B C D E FG RM Reality Probability Two at a time: Over all: 5± 2 0. 5 0. 25 3% Chance of 5 per day !!!
Previous Solution: Inventory Put a day of inventory at each process! WIP 5 Process A 5 B 5 C 5 5 D Total 25 E FG RM Variable Process 5± 2 WIP=throughput in bottleneck 5± 2
System Variability Takes Over--Chaos Inventory (WIP) quickly shifts position. Inventory manager/expediter tries to smooth it out. Distribution problems result. Costs go up. Process WIP A 3 B 0 C 10 D 8 E 4 Total 25 FG RM Variable Process 5± 2 25=3+10+4+8 5± 2
System Variability Takes Over--Chaos An Average of 5 means sometimes 3 and some times 7 Process WIP A 3 B 0 C 10 D 8 E 4 Total 25 FG RM Variable 5± 2 5± 2 Process Shifting work-in-process creates large queues at some locations. This makes work wait longer to be processed.
System Variability Takes Over--Chaos Process WIP A 3 B 0 C 10 D 8 E 4 Total 25 RM Variable 5± 2 5± 2 Process Shifting work-in-process creates large queues at some locations. This makes work wait longer to be processed. Other workstations can be starved for work. The work they could be doing is delayed because it is not there (B). They can’t take advantage of their extra capability. So. . . FG
System Variability Takes Over--Chaos Process WIP A 3 B 5 C 10 D 8 E 4 Total 25 ->X 30 30=25+5 RM Variable 5± 2 5± 2 Process So… Management Helps! Management puts in more work (Inventory) to give everyone something to do! Result: It takes longer and longer from time of release until final shipping. More and more delay!!!!!! FG
Attempts to Control WIP Use Kanban Cards-JIT WIP 5 Process A 5 B 5 C 5 D 5 Total 25 E RM Variable 5± 2 5± 2 Process Just-In-Time uses Kanban Cards to limit the queues building in the system. No more than 5 parts are allowed at any station. Looks good, but is it? FG
Effects of Inventory Limits on Production What does a Kanban card of 5 Mean? WIP 5 Process A 5 B 5 C 5 D 5 Total 25 E FG RM Variable Process 5± 2 7 Before Kanban 3 5± 2 5+/-2 Average = 5 After Kanban 2 Can’t exceed 5 5, 5 Average = 3, 5 = (3*5+5*0, 5)/5
Operation’s Dilemma Produce a lot Increase work -in- process Manage production effectively Costs & delivery in control Decrease work-inprocess Injection: Put a large inventory where its needed and low everywhere else! Assumption: We can’t both increase WIP and decrease WIP at the same time.
TOC Steps to Continuous Improvement Step 1. Identify the system’s constraint. Step 2. Exploit the system’s constraint. Step 3. Subordinate everything else to the above decision. Step 4. Elevate the system’s constraint. Step 5. If a constraint is broken (that is, relieved or improved), go back to Step 1. But don’t allow inertia to become a constraint.
Five Steps Applied to Flow Operations 12 WIP A B Total C D E RM FG 7 Five Focusing Steps 9 5 (5, 5) 8 7 Step 1. Identify the Constraint (The Drum) Step 2. Exploit the Constraint (Buffer the Drum) Step 3. Subordinate Everything Else (Rope) Step 4. Elevate the Constraint ($? ) Step 5. If the Constraint Moves, Start Over 6 12
Understanding Buffers WIP Total 12 parts/5 parts per day=2. 5 Days A B C D E FG RM 7 9 5 8 6 • The “Buffer” is Time! • In general, the buffer is the total time from work release until the work arrives at the constraint. • Contents of the buffer ebb and flow within the buffer • If different items spend different time at the constraint, then number of items in the buffer changes • but Time in the buffer remains constant.
We need more than one Buffer Raw Material Buffer A B C D E Finished Goods Buffer FG RM 7 9 5 8 6 There is variability in the Constraint. To protect our delivery to our customer we need a finished goods buffer. There is variability in our suppliers. We need to protect ourselves from unreliable delivery.
Buffer Time is Constant-Predictable Raw Material Buffer A B C D E Finished Goods Buffer FG RM Raw Material Buffer 2 Days 7 9 Constraint Buffer 2. 5 Days 5 8 6 Finished Goods Buffer 1 Day Processing Lead Time is Constant
Buffer Management Constraint Buffer WIP A Total 12/5=2. 5 Days B C D E RM FG 7 WO 21 WO 20 WO 19 WO 18 9 WO 17 WO 16 WO 15 WO 14 5 8 WO 13 WO 12 WO 11 WO 10 2. 5 Days Time until Scheduled at Constraint 0 6 • The Constraint is scheduled very carefully • Buffer Managed by location • Individual activities in the buffer are not scheduled
Problem Identification RM A B C D E RM WO 19 Delayed Parts FG 7 WO 21 WO 20 WO 19 WO 18 2. 5 Days 9 WO 17 WO 16 WO 15 WO 14 5 8 6 Constraint schedule is in jeopardy! (Red Zone Hole) WO 13 WO 12 WO 11 WO 10 Watch WO 14 (Yellow) 0 Time until Scheduled at Constraint WO 19 OK (Green) Green
Additional Buffers Constraint Buffer (as we discussed) • Protects the Constraint from running out of work Finished Goods Buffer • Protects customer delivery from Constraint variation Raw Material Buffer • Protects the Release of material from suppliers Assembly Buffer • Facilitates speedy flow of products
Additional Buffers Ropes Buffer Types: Constraint FG RM Assembly WIP Constraint Finished goods A B C D E RM FG 7 9 5 F G H 8 7 6 8 6 RM Raw Material Assembly
Manufacturing is an integrating discipline TOC Thinking Processes Physical Systems Behavior People Organizations Performance Measurement Assignments Quality Operations Optimization Simulation Decisions Reliability Supply Chain Finance Capital Projects Uncertainty Investment Measures Projects Full Theory Scheduling Manage Quality Design for Experiments Strategy Corporate Departmental Subordination Focus
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