Texas A&M Industrial Engineering 9/23/99

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1 anufacturing System anufacturing System Planning and Analysis Characterized by: Number of machines Number of part types Part routes through the system Processing times achine setups emand patterns Raw material/component availability Equipment layout/configuration Operator availability Parts achines Interested in: Lead time for products Cost of processing ecisions include: System configuration Scheduling methods Product esign Functional analysis esign for X Process planning System esign Capacity planning Layout design System Operation Production planning Scheduling 9/23/99 anufacturing Systems Planning and Analysis 1 9/23/99 anufacturing Systems Planning and Analysis 2 anufacturing System esign anufacturing System Operation Resource requirements anufacturing System esign Resource layout aterial flow Buffer capacity Operation ecomposition Planning eciding what to do Scheduling eciding when to do what you planned Execution Carrying out the planned tasks according to the schedule Hierarchical System Structure Shop Workstation Equipment 9/23/99 anufacturing Systems Planning and Analysis 3 9/23/99 anufacturing Systems Planning and Analysis 4 Principles of anufacturing Systems odels Little s Law WIP = Production Rate * hroughput ime atter is conserved Larger scope implies reduced reliability Objects decay Exponential growth in complexity components, N states ==> N possible system states echnology advances System components appear to behave randomly Limits of (Human) rationality Combining, simplifying, and eliminating save time, money, and energy A model is a description of a system odel s purpose is for understanding learning improving/optimizing decision making ypes of models Physical athematical A set of mathematical equations and/or logical relationships used to describe a system 9/23/99 anufacturing Systems Planning and Analysis 5 9/23/99 anufacturing Systems Planning and Analysis 6 INEN Introduction to anufacturing Systems 1

2 athematical odels Solution Concepts Prescriptive he model determines how to set the decision variables to optimize the system s performance escriptive iven a set of values for the decision variables, the model estimates the system s performance Characteristics Objective Why are you modeling? What issues are being addressed? Constraints ime People Expertise Information Budget Prescriptive athematical programming Heuristic procedures escriptive Queueing models Simulation 9/23/99 anufacturing Systems Planning and Analysis 7 9/23/99 anufacturing Systems Planning and Analysis 8 Solution Concepts Solution Concepts athematical Programming minimize or maximize subject to: g ( x, x,..., x ) b n 1 g ( x, x,..., x ) b n 2 g ( x, x,..., x ) b 1 2 m n m f ( x, x,..., x ) 1 2 where stands for one of the relations, =, or. n Heuristic Procedures Rational method that attempts to find a good solution to a (typically math programming) model. Evaluation Quality of solution istance from optimal Bounds Effort expended generating a solution Computation time/complexity emory requirements 9/23/99 anufacturing Systems Planning and Analysis 9 9/23/99 anufacturing Systems Planning and Analysis 10 Solution Concepts (cont.) Solution Concepts (cont.) Queueing Analysis of system behavior based on long-run average performance Often requires simplifying assumptions to get a tractable model Quickly generates performance results for a given system Population of customers Customers arriving Queue Queueing system Customer in service Server Customers departing Simulation Experimental model mimics events that occur in the real system Provides detailed performance results for a given system Allows experimentation by running the model with different operating parameters or control logic Sensitivity analysis Robustness Requires extensive modeling effort Initial design and modeling Verifying that the model performs as intended or specified Validating that the model matches the real-world situation that is being modeled and studied Requires extensive computational effort to generate useful results 9/23/99 anufacturing Systems Planning and Analysis 11 9/23/99 anufacturing Systems Planning and Analysis 12 INEN Introduction to anufacturing Systems 2

3 Verification and Validation Interpretation of Results System ata for model input Real System Validation odel: Implementation Verification Validation odel: Specification Care must be taken when interpreting results with respect to the real system Approximation odel Approximation (Askin and Standridge, 1993, p.25) Solution 9/23/99 anufacturing Systems Planning and Analysis 13 9/23/99 anufacturing Systems Planning and Analysis 14 anufacturing Systems Overview Product esign Product esign Process Planning Production System esign Production Planning Operational Planning Shop Floor Control Execution Idea Understanding and identifying customer needs Initial esign Feasibility study to determine initial functionality Prototype arket Research arket potential, economic analysis, strategic assessment esign Refinement Functional specifications etailed Specifications etailed design considering functions, quality/reliability, manufacturing, etc. Idea eneration (Product esign) Feasibility Study (Performance Specifications) Preliminary esign (Prototype) Final esign (Final esign Specifications) Process Planning (anufacturing Specifications) 9/23/99 anufacturing Systems Planning and Analysis 15 9/23/99 anufacturing Systems Planning and Analysis 16 Product esign (cont.) Product esign (cont.) Functional analysis Customer specifications Product reliability esign for X anufacture or Assembly Simplification, standardization, modularization esting Repair Robustness to variations Concurrent engineering Consider how product will be manufactured (process and production planning) during design phase Reduce cost and time to market 9/23/99 anufacturing Systems Planning and Analysis 17 Computer-Aided esign Use of computer graphics to assist in the creation, modification, and analysis of a design Common uses eometric modeling Automated drafting and documentation Engineering analysis esign analysis CA/ eneration of manufacturing instructions directly from CA design data 9/23/99 anufacturing Systems Planning and Analysis 18 INEN Introduction to anufacturing Systems 3

4 Product Lifecycle Production System Lifecycle Product (Consumer) Perspective Inception esign Production Use aintenance and repair isposal Reuse, recycle, scrap Sales Production System (anufacturer) Perspective esign Ramp-up aturity ecline ime Lifecycle Inception esign Construction Startup Use Closure Relationship to product lifecycle ypically production system lifecycle is longer than an individual product s lifecycle Production system will revert to earlier stages in its lifecycle when new products are introduced Extent and cost depends on system flexibility 9/23/99 anufacturing Systems Planning and Analysis 19 9/23/99 anufacturing Systems Planning and Analysis 20 anufacturing Systems Overview Production System esign Product esign Process Planning Production System esign Production Planning Operational Planning Shop Floor Control Execution ake vs. Buy ecision Capacity Planning echnology Acquisition Alternative System Configurations Production Cell Formation Part ype Selection Facility Layout 9/23/99 exas A& Computer Aided anufacturing 21 9/23/99 exas A& Computer Aided anufacturing 22 ake or Buy ecision Simple ake vs. Buy odel A new component is needed and we need to determine how we will acquire this component Purchase the component from outside Produce the component in-house Some combination of purchasing/producing Assume the following: We can purchase the component for c 1 per unit. We can produce it internally for c 2 < c 1 after an initial (fixed) cost of k to expand production capacity. Should you make or buy the component? 9/23/99 exas A& Computer Aided anufacturing 23 Cost to purchase x units, y 1 = (x c 1 ) Cost to produce x units, y 2 = k + (x c 2 ) otal cost y = c x 1 1 x b y2 = k + c2 x # of units y1 = y2 c x = k + c x 1 b 2 k xb = c c 1 2 x b is the point of indifference or the break-even point. 9/23/99 exas A& Computer Aided anufacturing 24 b INEN Introduction to anufacturing Systems 4

5 Problems with the Simple odel Production System esign Are fixed costs fixed? Using existing resources? Are variable costs constant over time? How do you compute variable costs? Is demand deterministic? What if the machine(s) produces multiple products? efine Resource Requirements - Capacity Planning What types and how many? achine/equipment ooling, fixtures, etc. People Arrange and Configure Resources Facility Location Facility esign Layout aterial Handling System Production Allocation 9/23/99 exas A& Computer Aided anufacturing 25 9/23/99 exas A& Computer Aided anufacturing 26 Capacity Planning Capacity Planning echnical Capability What are the capabilities of the factory? Processes, technologies, know-how Physical limitations of what can be produced What activities can be performed? Physical Capacity How much product can be produced in a given period of time? Equipment, tooling, fixturing, etc. Human resources Factors affecting capacity Processing rate Available time Breakdowns/Repairs Setups/Changeovers Operator unavailability aterial unavailability 9/23/99 exas A& Computer Aided anufacturing 27 9/23/99 exas A& Computer Aided anufacturing 28 Cellular Configurations/Layouts Cell Formation Job Shop Cellular Assigning parts and machines to groups or cells. Want to assign parts and machines to cells such that the part flow between cells is minimized and the utilization of machines within cells is high. 9/23/99 exas A& Computer Aided anufacturing Lab 29 9/23/99 exas A& Computer Aided anufacturing 30 INEN Introduction to anufacturing Systems 5

6 Production Flow Analysis (PFA) Production Flow Analysis Production Flow Analysis (Burbidge, 1989) is designed to find a complete division of parts into families and also a complete division of existing machines into groups by analyzing the process routes for individual parts. Coding schemes and distance-based grouping methods emphasize the capture of part attributes, thus helping to develop groups based on part similarity, but provide no information as to the set of machines that should be assigned to process the groups. he basic idea is to create a part-machine incidence matrix and to identify those parts that required the same or a similar set of machines and to bring these together into clusters. achine-part incidence matrix A matrix of binary elements where each row represents a machine and each column represents a part. A value of 1 for element m ij indicates that machine i is required by part j. 9/23/99 exas A& Computer Aided anufacturing 31 9/23/99 exas A& Computer Aided anufacturing 32 Part-achine Incidence atrix Partitioning of the Part-achine Incidence atrix part 3 is processed on machine 1 Part (p) achine (m) Note: he P- matrix does not explicitly consider the sequence of machine visits for the individual parts (i.e., the individual part routes) Part (p) achine (m) Voids Exceptional elements 9/23/99 exas A& Computer Aided anufacturing 33 9/23/99 exas A& Computer Aided anufacturing 34 Rearranged Partition Perfect Clusters Part (p) achine (m) Voids Exceptional element Part (p) achine (m) No voids or exceptional elements. 9/23/99 exas A& Computer Aided anufacturing 35 9/23/99 exas A& Computer Aided anufacturing 36 INEN Introduction to anufacturing Systems 6

7 Voids and Exceptional Elements Facility Planning Voids - indicate that a machine assigned to a cell is not required by all parts assigned to that cell. Leads to large, inefficient cells and can potentially contribute to low utilizations. Exceptional elements - indicate that a part assigned to a cell requires processing by a machine not in the cell. his forces an inter-cell handling step and requires coordination between cells. he voids and exceptional elements created are dependent on the number and size of the diagonal blocks formed in the part-machine incidence matrix. Facilities Location Facilities Planning Facilities esign 9/23/99 exas A& Computer Aided anufacturing 37 9/23/99 exas A& Computer Aided anufacturing 38 Facility Planning Facility Layout Facilities Location ompkins et al., 1996 Facilities Planning Facility Systems esign Facilities esign Layout esign Handling Systems esign ake vs. Buy ecision What to produce in the facility Process Planning What resource types are needed Capacity Planning How many resources are needed Alternative System Configurations Strategic choice of configurations based on volume/variety Production Cell Formation How should resources be logically grouped Facility Layout Where should resources be located within the facility? 9/23/99 exas A& Computer Aided anufacturing 39 9/23/99 exas A& Computer Aided anufacturing 40 Facility Layout Facility Layout How should resources be arranged in a flow line configuration? Straight-line, U-shaped, Serpentine, etc. How should departments be arranged in a job shop configuration? 9/23/99 exas A& Computer Aided anufacturing 41 9/23/99 exas A& Computer Aided anufacturing 42 INEN Introduction to anufacturing Systems 7

8 Facility Layout Facility Layout odeling How should cells be arranged in a cellular manufacturing system? Cell 1 Cell 3 Cell 2 Cell 4 How should machines be arranged within cells? Level of detail Block plan Arrange departments within the facility area What are departments? etailed plan Layout of each individual workstation Structural plan Architectural Loading Utilities 9/23/99 exas A& Computer Aided anufacturing 43 9/23/99 exas A& Computer Aided anufacturing 44 Facility Layout odeling Facility Layout odeling Objective Support organization s goals aximize profit Layout goals inimize material handling cost inimize floor space aximize important adjacencies Allow for flexibility and expansion Constraints Floor space Area and configuration Columns Floor loadings Ceiling clearance heights epartments Area Shape Special requirements Unallowable Adjacencies Noise, fumes, chemical reactions 9/23/99 exas A& Computer Aided anufacturing 45 9/23/99 exas A& Computer Aided anufacturing 46 INEN Introduction to anufacturing Systems 8