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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

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production planning operations scheduling with applications in manufacturing and services
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
Literature

Book: Operations Scheduling with applications

in manufacturing and services

Authors: M. Pinedo, X. Chao

Handouts, also downloadable from website

slide3
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
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
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
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
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
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
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
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
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
Our approach

Scheduling problem

Problem formulation

Model

Solve with algorithms

Conclusions

scheduling models
Scheduling models
  • Job shop scheduling
  • Project scheduling
  • Flexible Assembly Systems
  • Lot sizing and scheduling
  • Workforce scheduling, staffing
  • Interval scheduling, reservation systems, timetabling
scheduling algorithms
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
    • tabu search
    • adaptive search
  • k-opt methods
  • genetic algorithms
  • neural networks
scheduling algorithms cont
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
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?)

slide17

Dispatching

Rules

Value

Objective

Function

Local

Search

Beam Search

Branch and Bound

CPU - Time

consideration of software companies w r t optimization techniques
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?

(Is an immediate answer required, or are long calculations allowed? Does customer accept complex solutions?)

online scheduling

offline scheduling

commercial packages
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
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
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
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
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