The Ultimate OM441 Midterm Review.pdf

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Department
Operations & Technology Management
Course
SMG OM 441
Professor
All Professors
Semester
Fall

Description
THE ULTIMATE OM441 MIDTERM REVIEW Chapter 1 • Supply Chain: All activities involved in the delivery of goods and services -- starting with creation and ending with extinction Two largest levers of supply chain performance is inventory and capacity • • Need models whfen production and allocation decisions matter • Supply Chain Decisions: • Strategic: Quarterly, Years -- MakeBuy Analysis, Outsourcing • Tactical: Weeks, Months, Quarters -- Sourcing Mix Allocation, Inventory Optimization • Operational: Days, Weeks -- Detailed scheduling, demand planning • Advanced Planning and Scheduling (APS): Demand planning, supply planning, production planning, available to promise • Manufacturing Execution Systems (MES): Determine what should be scheduled on an hourly or minute- by-minute schedule level • Operational problem solutions exceeds that for tactical and strategical models Operational problems occur in a time frame that can ignore variability • • Operational models can be formulated as deterministic problems • With the rise of outsourcing, importance of tactical planning increases and operational planning decreases • Tactical plans become main leverage points in the outsourced supply chain • Tactical models can occupy a problem space where variability can be appropriately characterized and managed Right approach is to make models as small as possible while still ensuring they provide value • • Find decoupling points between models so that they rely on common data and possess compatible inputs and outputs Chapter 2 • Every Supply Chain comprises of a system of materials and information flows responsible for converting inputs and outputs • Point of Leverage: observations have extreme value on one or more explanatory variable • Focus on one or more explanatory variable • Focus on the most important problems -- appropriate supply chain views should make the important problems self-evident Evaluate changes using the model • • When scoping a project, the goal is to define a problem largely but still making it traceable • Granularity: the level of detail we employ in the representation of the supply chain -- determine the bill of materials and level of process • Facility based view of supply chain: Visual • Pro: can easily describe the supply chain in a way non supple chain people will understand • Con: Cannot easily match products or processes to the supply chain map Echelon-based view of Supply Chain: A layer of supply chain that is distinct from its adjacent layers • • Pros: echelon based can clearly see the major functions of the supply chain • Con: don’t see the complexity, it’s “big picture new” • Stock Keeping Unit (SKU): location base view • Pro: maps mostly direct to decisions need to be made • Con: For realistic supply chain these figures are so large that they can be too detailed to yield sight Optimization Model Overview • Models solve a problem • Abstract reality to something that can be solved Default “There’s a model for that” • • Transform into a problem statement • Good models: 2 outcomes for something -- both outcomes are reasonable Elements of a Model 1. Decision Variables: steering wheel of a car -- Variables we have control over that affect our solution 2. Parameters: Inputs of the model-data -- Just there, reflect reality of operating environment 3. Intermediate Variable: Functions of decision variables and parameter -- Not needed of optimization but needed in absolute (necessary for model results) 4. Constraints: Limit decisions and intermediate variables -- no full freedom -- ALL HAVE CONSTRAINTS 5. Objective Function: Translate business-speak model to model-speak -- ex: maximize profits/minimize cost • All five elements together form a mathematical program • Types: Deterministic, linear, nonlinear, integer, etc • Ability to near a business problem then create something • Optimization cannot hit one spot, which is good because data does not have to be perfect, decisions do not have to be perfect #1 Rule for a good model • As simple as possible -- create the simplest • How simple? They should be the building blocks that are used with the other models Scope and Granularity • Scope: Where a model begins and ends • Granularity: The level of detail employed in the model’s representation of reality • You want the smallest scope possible and the least granularity possible • One model cannot do everything!! September 16, 2013 Lecture Capacity Utilization = [time required/time available] • • The formula is always required over available • *How you explain the solution is far more important than the number that you get -- You sell on the framework • Mutually Exclusive: don’t double count • Collectively Exhaustive: don’t leave
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