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Omm Cheatsheet

Essay by   •  September 2, 2019  •  Exam  •  1,772 Words (8 Pages)  •  2,992 Views

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Session 1

  1. Operations: how to make money by producing goods/services of VALUE to customers
  2. Business process flow: a collection of recurring economic activities that takes one or more kinds of inputs and creates an output that is of value to customer
  3. Management of business processes: build CAPABILITIES that OPTIMALLY convert inputs to outputs
  4. Order winners / four dimensions: Time / Price / Quality / Variety
  5. Inventory turns: how fast firms sell their inventory
  6. The operation quadrangle: Throughput / Cycle time / Inventory / Capacity
  7. Two objectives: audit questions (understanding a business process) & managerial levels (improving a business process, inherent tradeoffs)

Session 2

  1. Types of processes: Projects-church; Job shops-high tech model building; Batch processes-guitar; Line flows-BMW cars; Continuous processes-Paper
  2. As move from projects to continuous processes
  1. Volume & Tightness & commodity & focus on throughput & capital: up
  2. Variety & flexibility & uncertainty & labor & focus on CT: down
  1. NCC case
  1. Reduce truck queuing and overtime (make span) 🡪 add capacity
  2. Reduce truck queuing 🡪 add buffer space (bins)
  3. Product mix affects effective capacity
  4. As resources are added to a bottleneck, bottleneck ill shift to different resource
  1. Merton Trucks case
  1. Shadow prices: how much is one more unit of a resource worth (linear program solvers)

Session 3

  1. The goal: decrease INV & operation expense and increase throughput rate 🡨 eliminating variability and waste  
  2. Critical path: sequence of steps through which all jobs must pass, having the longest total time, including wait time
  3. Cycle time key facts: includes waiting times & it is a average & determined by critical path
  4. Customers should only see value-add
  5. In the presence of variable arrivals/service times
  1. Attempting to set throughput = capacity 🡪 system is unstable
  2. Throughput < capacity 🡪 system is stable & waiting occurs
  3. Waiting caused by 🡨 short-term surges in demand & short-term slumps in service
  1. A river analogy: lowering WIP inventory (too much space, missed due dates, larged lot sizes, long lead times, poor vendor quality, machine breakdowns, unreliable deliveries, scrap and rework)
  2. Traditional system: PUSH production – WIP is not explicitly limited
  1. Complex set of decisions
  2. Main feature: manager controls release rate
  1. New system: PULL production – a pull production syste is one that explicity limits the amount of WIP that can be in the system & information flows backward
  1. Reduced WIP and CT
  2. Smoother production flow (more predictable)
  3. More controllable system
  1. Push and pull are NOT make-to-order and make-to-stock
  2. Responsibility reversal
  1. Traditionally operators responsible for: throughput, management responsible for: quality
  2. TPS operators responsible for: quality, Management responsible for: throughput
  1. TPS/JIT summary
  1. All processes driven to be in control and capable
  2. Problems are natural: opportunities to learn
  3. Every activity must add value
  4. Heijunka (connect value chain from customers to suppliers)
  5. Human infrastructure (fast based vs. blame based)
  6. It is a system
  1. Problem of traditional flow line: imbalance / work in process / inflexible  
  2. Toyota case
  1. Andon: andon lamp to show the stopness of line
  2. Goesu: 5S
  1. Sort (Seiri): eliminate unnecessary tools
  2. Streamline (Seiton): arrange work for orderling flow, remove waste / non value add
  3. Shine (Seiso): clean the work area, keep it tidy and organized
  4. Standardize (Seiketsu): ensure iniform processes for interchangeability, regular maintenance
  5. Sustain (Shitsuke): ensure adherence to rules to prevent backsliding, visual workplace
  1. Heijunka: leveled production
  1. Benefits: Lowers std.dev to suppliers / Balances the line / Shortens response time to customers
  2. Requirement: Short setup/changeover times / Coordination with suppliers
  1. Jidoka: quality at the source & detect defect when it occurs (avoid mindless automation)
  2. Kaizen: continuous improvement (persistence in achieving JIT, Jidoka, and Heijunka)
  3. Kanban
  4. Poka yoke: fail-safe devices (avoiding the effects of distraction)
  5. Single minute exchange of dies (SMED): process improvement to reduce setup/changeover times

Session 4

  1. Why hold raw materials
  1. Variance 🡨 unreliable supplier & demand variance
  2. Economies of scale 🡨 quantity discounts & shipping/handling cost structure
  1. Why hold finished goods inventory
  1. Variance 🡨 demand
  2. Economies of scale 🡨 batches
  3. Shorter lead times to customers 🡨 make-to-stock vs. make-to-order
  1. Beer game
  1. Difficulty in controlling single supply chain lik
  2. Bullwhip effect: fluctuations in orders increase as move up the supply chain
  3. Cause of bullwhip effect: structure of supply chain itself
  4. Mitigating the bullwhip effect
  1. Decentralized links
  2. Reduce shipping/information delays
  3. Decrease demand variance within supply chain

Session 5

  1. Goal of inventory management: reduce cost, improve service
  2. Why hold inventory
  1. SAFETY STOCK: Absorb variability 🡨 demand & lead time
  2. CYCLE STOCK: Economies of scale / fixed costs 🡨 delivery & production & ordering
  1. Fill rate: fraction of demand satisfied from on-hand inventory & more accurate – sensor demand
  2. Service level: use when cannot track on demand
  3. Tradeoffs
  1. Optimal order size (Q): inventory holding vs. ordering cost 🡪 CYCLE STOCK
  2. Optimal reorder point (R): inventory holding vs. stock-out costs 🡪 SAFETY STOCK
  1. Economic order quantity (EOQ)
  2. Laws of forecasting: forecasts are always wrong, forecasts always change, the further into the future, the less reliable the forecast will be, aggregate forecasts are more accurate
  3. Barilla case
  1. Effects/costs of fluctuations
  1. Manufacturing: inefficient sequencing, excess finished goods inventory
  2. Distribution: excess warehousing resources, excess transportation costs
  1. Just-in-Time Distribution (JITD)
  1. Barilla will get daily distributor inventory and shipment data by SKU
  2. Barilla controls shipping decisions
  1. Lessons
  1. Aligning goals and incentives
  2. Improving information accuracy
  3. Supplier partnerships

Session 6

  1. Contribution: Cout(B=order, D=demand) = sales value + salvage value – costs
  2. Expected contribution: E[Cont/B=order] = Cont1 * prob1 + Cont2 * prob2+…
  3. Optimal order quantity: the first one that attains the higest expected contribution in cumulative probability chart
  4. The newsvendor model
  1. Not restricted to inventory decisions 🡨 single period decision under uncertainty
  1. Revenue management: more complex, newsvendor-like decisions
  2. Confederated pulp & paper case
  3. Pooling / postponement: postponing product differentiation to aggregate demand streams
  1. Forms of pooling
  1. Virtual centralization: car dealer
  2. Specialization: toy store vs. baby store
  3. Component commonality
  4. Product substitution
  5. Postponement
  1. Holds on non-identical means / std.dev
  2. Holds with non-normal distribution
  3. Effect decreases with + correlation / increases with – correlation
  1. Warehousing: functions & strategy
  2. Distribution: routing & delivery
  3. Cross-docking: do not hold inventories for long time, just for few hours / min warehouse / provides only one of the traditional warehouse functions: merge/sort/limited repack 🡪 CT down, INV down
  4. Source of variability
  1. Demand variance: seasonality, promotions
  2. Process variance: machine/worker variation
  3. Service interruptions: equipment breakdown, lunch break
  4. Quality problems: rework, batching
  5. Supply variance: unreliable suppliers
  6. Over-reaction in supply chain: bullwhip effect
  1. Response to variability
  1. Mitigate the source
  2. Manage the system

Main Lessons From The Goal Book

three operational measurements:

•        Throughput: the rate at which the system generates money through sales net of variable costs. This corresponds to the value added by the system.

•        Inventory: “all the money that system has invested in purchasing things which it intends to sell,” This was later expanded to include all investment such as plant, property, equipment etc.

•        Operating Expense: “all the money the system spends in order to turn inventory into throughput.” These fixed costs like rent and salaries are incurred whether or not throughput increases or decreases.

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