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Operations Management Theory of Constraints (TOC) Handout Dr. Ahmad Syamil

Operations Management Theory of Constraints (TOC) Handout Dr. Ahmad Syamil. Theory of Constraints (TOC). A management philosophy developed by Dr. Eliyahu Goldratt that can be viewed as three separate but interrelated areas: Logistics, e.g., buffer management

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Operations Management Theory of Constraints (TOC) Handout Dr. Ahmad Syamil

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  1. Operations ManagementTheory of Constraints (TOC)HandoutDr. Ahmad Syamil

  2. Theory of Constraints (TOC) A management philosophy developed by Dr. Eliyahu Goldratt that can be viewed as three separate but interrelated areas: • Logistics, e.g., buffer management • Performance measurement, e.g., throughput • The five focusing steps

  3. Related Terms • Constraint management • Synchronous/synchronized manufacturing (General Motors) • Optimized Production Technology (OPT) software • Drum-Buffer-Rope system • Throughput technology

  4. Relationships Between Throughput, Inventory, Operating Expenses and Profit Transparency 17.10 (Exhibit 17.9)

  5. Exhibit 17.10 A Constrained Production Process

  6. Exhibit 17.10 (without TOC) • A has a higher profit/unit --> max. A • Production process for A: • 100 units x 0.4 hours/unit = 40 hours • Remaining time for B: • 60 hours - 40 hours = 20 hours • 20 hours / (0.2 hours/unit) = 100 units • Profit: • For A: 100 units x $80/unit = $8,000 • For B: 100 units x $50/unit = $5,000 Total = $13,000

  7. Types of Constraints • Internal Resource = resource within organization which limits performance • Market = market demand less than production capacity • Policy = Any policy that limits performance Transparency 17.11

  8. The Five Focusing Steps in Theory of Constraints 1. Identify the system’s constraints 2. Determine how to exploit system’s constraints 3. Subordinate everything else to the decision made in step 2 4. Elevate the constraints in order to reach higher performance level 5. Go back to step 1. Do not let inertia become new constraint Transparency 17.12

  9. Constrained Resource Utilizationfor Each Product Transparency 17.13 (Exhibit 17.11)

  10. Exhibit 17.10 (with TOC) • B has a higher profit/hour --> max.B. • Production process for B: • 200 units x 0.2 hours/unit = 40 hours • Remaining time for A: • 60 hours - 40 hours = 20 hours • 20 hours / (0.4 hours/unit)= 50 units • Profit: • For A: 50 units x $ 80/unit = $4,000 • For B: 200 units x $50/unit = $10,000 Total = $14,000 vs $13,000 (without TOC)

  11. Effect of Increasing Size of Process Batch Transparency 17.14 (Exhibit 17.12)

  12. Effect of DecreasingTransfer Batch Size Transparency 17.15 (Exhibit 17.13)

  13. The Drum = Constraint = Bottleneck Operation • It sets the rate of all other operations to match its own • The Buffer = Inventory • 1. Time buffers = constraint buffers = raw materials or work in process (WIP) inventory. Location: • a. Before bottleneck processes/operations • b. At locations where parts from the bottleneck are combined with parts from other processes/operations • Function: To prevent those operations from having to shut down (=“starving”= no materials) due to problems at non-bottleneck resources. • 2. Stock buffers = shipping buffers = inventories of finished goods held in anticipation of market demand. Location: After the final operation/assembly process • The Rope = linkage = communication to prevent the buildup or the shortage of inventory. • Examples: formal production schedule and informal discussions between employees. Locations: (1) a rope communicating from finished-goods inventory back to the drum to increase or decrease output, and (2) a rope from the drum back to the material release point, specifying how much material is needed. TOC: Drum, Buffer, and Rope

  14. Network Flow Diagramwith One Bottleneck Transparency 17.16 (Exhibit 17.14)

  15. Comparison ofMRP, JIT and TOC MRP JIT TOC Loading of operations Batch sizes Importance of data accuracy Speed of scheduled development Flexibility Cost Goals Planning focus Production basis Checked by capacity requirements Planning afterward One week or more Critical Slow Lowest Highest Meet demand Have doable plan Master schedule Plan Controlled by kanban system Small as possible Unnecessary Very fast Highest Lowest Meet demand Eliminate waste Final assembly schedule Need Controlled by bottleneck operation Variable to exploit constraint Critical for bottleneck and feeder operations Fast Moderate Moderate Meet demand Maximize profits Bottleneck Need and plan Transparency 17.17 (Exhibit 17.15)

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