Production planning operations scheduling with applications in manufacturing and services Erwin Hans T M OMST BB 235 tel 3523 e w hans sms by rwi74592

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									     Production planning:
      operations scheduling
       with applications in
    manufacturing and services
     Erwin Hans (T&M-OMST)
             BB-235, tel. 3523,
         e.w.hans@sms.utwente.nl
     Johann Hurink (TW-STOR)
        J.L.Hurink@math.utwente.nl
Faculty of Technology and Management
          University of Twente
      Enschede, The Netherlands
Literature
Book: Operations Scheduling with applications
      in manufacturing and services
Authors: M. Pinedo, X. Chao

Handouts, also downloadable from website
 Exam
These methods must be learned entirely
(one or two questions about these will be in the exam):
• adaptive search
• branch-and-bound, beam-search
• shifting bottleneck

The idea (approach) and application of all other discussed
methods must be learned (i.e., no formulas)

One question will be asked about the software demonstration

Aside from the discussed chapters from the book,
the handouts must be learned
Scheduling: definition

Allocation of jobs to scarce resources

the types of jobs and resources depend on
  the specific situation

Combinatorial optimization problem
   maximize/minimize objective
   subject to constraints
Application areas
Manufacturing, e.g.:
  job shop / flow shop scheduling
  workforce scheduling
  tool scheduling
Services, e.g.:
  Hotel / airline reservation systems
  Hospitals (operating rooms)
Transportation and distribution, e.g.:
  vehicle scheduling, and routing
  railways
Application areas (cont.)
Information processing and communications:
  CPU’s, series and parallel computing
  call centers
Time-tabling, e.g.:
  lecture planning at a University
  soccer competition
  flight scheduling
Warehousing, e.g.:
  AGV scheduling, and routing
Maintenance, e.g.:
  scheduling maintenance of a fleet of ships
Scheduling in manufacturing
Due to increasing market competition,
  companies strive to:
shorten delivery times
increase variety in end-products
shorten production lead times
increase resource utilization
improve quality, reduce WIP
prevent production disturbances (machine
  breakdowns)
--> more products in less time!
Different types of manufacturing
control

Make and assemble to stock
Make to stock, assemble to order
Make to order
Engineer to order
    Scheduling in a manufacturing
   planning and control framework
Long range forecasting and sales planning
Facility and resources planning
Demand management, aggregate and
 workforce planning
Order acceptance and resource group loading

Shop floor scheduling, workforce scheduling
Relations with other management
areas

Product and process design
Process planning
Inventory management and materials
 planning
Purchasing and procurement
 management
Warehousing and physical distribution
Scheduling in services
Workforce Scheduling in
  Call Centers
  Hospitals
  Employment agencies
  Schools, universities
Reservation Systems in
  Airlines
  Hotels
  Car Rentals
  Travel Agencies
Postal services
Our approach

       Scheduling problem
                  Problem formulation
               Model

                  Solve with algorithms

          Conclusions
Scheduling models

Job shop scheduling
Project scheduling
Flexible Assembly Systems
Lot sizing and scheduling
Workforce scheduling, staffing
Interval scheduling, reservation systems,
 timetabling
 Scheduling algorithms
General solution Techniques:
Mathematical programming
  linear, non-linear, (mixed) integer programming
Exact methods (enumeration)
  branch-and-bound
  dynamic programming
  cutting plane / column generation methods
Local search methods, heuristics
  simulated annealing k-opt methods
  tabu search         genetic algorithms
  adaptive search     neural networks
 Scheduling algorithms (cont.)
Heuristics
  dispatching rules
  composite dispatching rules
  beam-search
Decomposition Techniques
  Temporal decomposition (rolling horizon
   approach)
  Machine decomposition (Shifting Bottleneck)
Hybrid Methods
  combined usage of scheduling methods
 Important characteristics of
 optimization techniques
Quality of Solutions Obtained
 (How Close to Optimal?)
Amount of CPU-Time Needed
 (Real-Time on a PC?)
Ease of Development and Implementation
 (How much time needed to code,
  test, adjust and modify)
Implementation costs
 (Are expensive LP-solvers required?)
            Dispatching
               Rules
 Value
Objective                         Local
Function                          Search

            Beam
            Search        Branch and Bound
                           CPU - Time
 Consideration of software companies
 w.r.t. optimization techniques
Implementation costs
  (Are expensive LP-solvers required? Easy to
  implement?)

vs.

What solution quality does the customer
 require?        online scheduling  offline scheduling
  (Is an immediate answer required, or are long
  calculations allowed? Does customer accept
  complex solutions?)
 Commercial Packages
 ERP-SYSTEMS
   SAP, Baan, JD Edwards, People Soft, Navision, MFG Pro
 GENERAL OPTIMIZATION
   Ilog, Dash, MINTO, OSL (IBM), XPRESS-MP, OML, XA
 GENERAL SCHEDULING
   I2, Cybertec, AutoSimulation, IDS Professor Scheer,
    ORTEC
 SCHEDULING OIL AND PROCESS INDUSTRIES
   Haverly Systems, Chesapeake, Finity, ORTEC
 SCHEDULING CONSUMER PRODUCTS
   Manugistics, Numetrix
 SCHEDULING WORKFORCE IN CALL CENTERS
   AIX, TCS, Siebel
 Decision Support Systems
Important issues in design of DSS:
Database design and management
Data collection (e.g. barcoding system)
Module Design and Interfacing
GUI Design (Gantt-charts, etc.)
Design of link between GUI and algorithm library
  (data organization before transfer)
Internal Re-optimization
External Re-optimization
 GUI’S should allow:
Interactive Optimization
  Freezing Jobs and Re-optimizing
  Creating New Schedules by Combining Different
   Parts from Different Schedules
Cascading and Propagation Effects
  After a Change or Mutation by the User, the system:
  does Feasibility Analysis
  takes care of Cascading and Propagation Effects,
  does Internal Re-optimization
Graphics user interfaces for
scheduling production processes


Gantt Chart Interface
Dispatch List Interface
Time Buckets (resource capacity loading)
Throughput Diagrams
Time tables
Important objectives to be
displayed
Due Date Related
  Number of late jobs
  Maximum lateness
  Average lateness, tardiness
Productivity and Inventory Related
  Total Setup Time
  Total Machine Idle Time
  Average Time Jobs Remain in System, WIP
Resource usage
  resource shortage

								
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