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Manufacturing Systems III. Chris Hicks MMM Engineering Email: [email protected] Assessment. End of year examination 2.5 hours duration Answer 4 questions from 6. Manufacturing Systems III. Manufacturing Strategy JIT Manufacturing Manufacturing Planning and control

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Manufacturing systems iii

Manufacturing Systems III

Chris Hicks MMM Engineering

Email: [email protected]



  • End of year examination

  • 2.5 hours duration

  • Answer 4 questions from 6

Manufacturing systems iii1

Manufacturing Systems III

  • Manufacturing Strategy

  • JIT Manufacturing

  • Manufacturing Planning and control

  • Company classification

  • Modelling & Simulation

  • Queuing theory (CFE)

Manufacturing strategy

Manufacturing Strategy

Manufacturing systems iii


  • Hill, T (1986),”Manufacturing Strategy”, MacMillan Education Ltd., London. ISBN 0-333-39477-1

Manufacturing strategy1

Manufacturing Strategy

  • Long term planning

  • Alignment of manufacturing to satisfy market requirements

Significance of manufacturing

Significance of Manufacturing

  • Manufacturing often responsible for majority of capital and recurrent expenditure

  • Long term nature of many manufacturing decisions makes them of strategic importance

  • Manufacturing can have a large impact on competitiveness

Manufacturing strategy2

Manufacturing Strategy

  • Make / buy

  • Process choice

  • Technology

  • Infrastructure, systems, structures & organisation

  • Focus

  • Integration with other functions

Strategy development

Strategy Development

  • Define corporate objectives

  • Determine marketing strategies to meet these objectives

  • Assess order qualifying and order winning criteria for products

  • Establish appropriate processes

  • Provide infrastructure

Identifying market requirements

Identifying Market Requirements

  • Order Qualifying criteria

  • Order winning criteria

  • Order losing criteria

Manufacturing influences

Manufacturing Influences

  • Costs

  • Delivery

  • Quality

  • Demand flexibility

  • Product range

  • Standardisation / customisation

Profile analysis

Profile Analysis

  • Assess match between market requirements and current performance

  • Identify changes required to manufacturing system

Market requirements

Market Requirements


V Imp.






Other factors

Manufacturing systems iii

Current Performance


V Imp.






Other factors

Manufacturing systems iii

Market requirement

Achieved performance

V Imp.







Other factors

Process choice

Process Choice

  • Type of process: project, jobbing, batch,line

  • Flexibility

  • Efficiency

  • Robustness wrt product mix / volume

  • Unique / generic technology?

  • Capital employed

  • How do processes help competitiveness?

Manufacturing structure

Manufacturing Structure

  • Layout: functional or cellular?

  • MTS / MTO

  • Flexibility of workforce

  • Organisation, team working etc.

  • Breakdown of costs

  • HRM issues



  • Relative importance, present and future

  • Mix

  • Complexity

    • Product structure

    • Concurrency

    • Standardisation / customisation

  • Contribution

Measures of performance

Measures of performance

  • What are they?

  • Frequency of measurement

  • Comparison with plan.

  • Orientation: product / process / inventory

  • Integration with other functions



  • Manufacturing planning & control

  • Sharing information / knowledge

  • CAD / CAM

  • Accounting systems

  • Quality systems

  • Performance measurement

Case studies

Case studies

  • Heavy engineering

    • PIP teams, simplification, value engineering, cellular manufacturing

  • Automotive supplier

    • “world class” but still relatively low productivity compared with Japanese sister company. Why?

Manufacturing systems iii

“Manufacturing is a business function rather than a technical function. The emphasis should be on supporting the market” Terry Hill (1996)

Just in time manufacturing

Just-in-Time Manufacturing



  • APICS (1987),”APICS Dictionary”, American Production and Inventory Control Society, ISBN 0-935406-90-S

  • Vollmann T.E., Berry W.L. & Whybark D.C. (1992),”Manufacturing Planning and Control Systems (3rd Edition)”, Irwin, USA. ISBN 0-256-08808-X

  • Browne J., Harhen J, & Shivnan J. (1988),“Production Management Systems: A CIM Perspective”,Addison-Wesley, UK, ISBN 0-201-17820-6

Just in time manufacturing1

Just-in-Time Manufacturing

“In the broad sense, an approach to achieving excellence in a manufacturing company based upon the continuing elimination of waste (waste being considered as those things which do not add value to the product). In the narrow sense, JIT refers to the movement of material at the necessary time. The implication is that each operation is closely synchronised with subsequent ones to make that possible”

APICS Dictionary 1987

Just in time


  • Arose in Toyota, Japan in 1960s

  • Replacing complexity with simplicity

  • A philosophy, a way of thinking

  • A process of continuous improvement

  • Emphasis on minimising inventory

  • Focuses on eliminating waste, that is anything that adds cost without adding value

  • Often a pragmatic choice of techniques is used

Just in time goals

Just-in-Time Goals

  • “Zero” inventories

  • “Zero” defects

    • Traditional Western manufacturers considered Lot Tolerance Per Cent Defective (LTPD) or Acceptable Quality Levels (AQLs)

  • “Zero” disturbances

  • “Zero” set-up time

  • “Zero” lead time

Just in time goals1

Just-in-Time Goals

  • “Zero” transactions

    • Logistical transactions: ordering, execution and confirmation of material movement

    • Balancing transactions: associated with planning that generates logistical transactions - production control, purchasing, scheduling ..

    • Quality transactions: specification, certification etc.

    • Change transactions: engineering changes etc.

  • Routine execution of schedule day in -day out

Benefits of jit

Benefits of JIT

  • Reduced costs

  • Waste elimination

  • Inventory reduction

  • Increased flexibility

  • Raw materials / parts reduction

  • Increased quality

  • Increased productivity

  • Reduced space requirements

  • Lower overheads

Just in time1


JIT links four fundamental areas

  • Product design

  • Process design

  • Human / organisational issues

  • Manufacturing planning and control

Manufacturing systems iii

Vollmann et al 1992

Product design

Product Design

  • Design for manufacture

  • Design for assembly

  • Design for automation

  • Design to have flat product structure

  • Design to suit cellular manufacturing

  • Achievable and appropriate quality

  • Standard parts

  • Modular design

Process design

Process Design

  • Set-up / lot size reduction

  • Include “surge” capacity to deal with variations in product mix and demand

  • Cellular manufacturing

  • Concentrate on low throughput times

  • Quality is part of the process, autonomation, machines with built in capacity to check parts

  • Continuous quality improvement

  • No stock rooms - delivery to line/cell

  • Flexible equipment

  • Standard operations

Human organisational elements

Human / Organisational Elements

  • Whole person concept, hiring people, not just their current skills / abilities

  • Continual training / study

  • Continual learning and improvement

  • Workers capabilities and knowledge are as important as equipment and facilities

  • Workers cross trained to take on many tasks: process operation, maintenance, scheduling, problem solving etc.

  • Job rotation / flexibility

  • Life time employment / commitment?

Organisational elements

Organisational Elements

  • Little distinction between direct / indirect labour

  • Activity Based Cost (ABC) accounting

  • Visible team performance measurement

  • Communication / information sharing

  • Joint commitment

Jit techniques

JIT Techniques

  • Manufacturing techniques

  • Production and material control

  • Inter-company JIT

  • Organisation for change

Manufacturing techniques

Manufacturing Techniques

  • Cellular manufacturing

  • Set-up time reduction

  • Pull scheduling

  • Smallest machine concept

  • Fool proofing (Pokayoke)

  • Line stopping (Jikoda)

  • I,U,W shaped material flow

  • Housekeeping

Group technology cellular manufacturing

Group Technology / Cellular Manufacturing

  • Improved material flow

  • Reduced queuing time

  • Reduced inventory

  • Improved use of space

  • Improved team work

  • Reduced waste

  • Increased flexibility

Set up time reduction

Set-up Time Reduction

  • Single minute exchange of dies (SMED) - all changeovers < 10 mins.

    1.Separate internal set-up from external set-up. Internal set-up must have machine turned off.

    2.Convert as many tasks as possible from being internal to external

    3.Eliminate adjustment processes within set-up

    4.Abolish set-up where feasible

    Shingo, S. (1985),”A Revolution in Manufacturing: the SMED System”, The Productivity Press, USA.

Basic steps in a traditional set up operation

Basic Steps in a Traditional Set-up Operation

1.Preparation, after process adjustments, checking of materials and tools (30%).

2. Mounting and removing blades, tools and parts (5%) Generally internal.

3. Measurements, settings and calibration (15%) includes activities such as centring, dimensioning, measuring temperature or pressure etc.

4. Trial runs and adjustments (50%) - SMED

Typical proportion of set-up time given in parenthesis.

Set up analysis

Set-up Analysis

  • Video whole set-up operation. Use camera’s time and date functions

  • Ask operators to describe tasks. As group to share opinions about the operation.

Three stages of smed

Three Stages of SMED

1.Separating internal and external set-up

doing obvious things like preparation and transport while the machine is running can save 30-50%.

2.Converting internal set-up to external set-up

3.Streamlining all aspects of the set-up operation

Separating internal and external set up

Separating Internal and External Set-up



A board which shows if any operator on the line has difficulties

  • Red - machine trouble

  • White - end of a production run

  • Blue - defective unit

  • Yellow - set-up required

  • Line-stop - all operators can stop the line to ensure compliance with standards

  • Flexible workers help each other when problems arise

Jit material control

JIT Material Control

  • Pull scheduling

  • Line balancing

  • Schedule balance and smoothing (Heijunka)

  • Under capacity scheduling

  • Visible control

  • Material Requirements Planning

  • Small lot & batch sizes

Pull systems

“Pull” Systems

  • Work centres only authorised to produce when it has been signalled that there is a need from a user / downstream department

  • No resources kept busy just to increase utlilisation


  • Small lot-sizes

  • Low inventory

  • Fast throughput

  • Guaranteed quality

Pull systems1

Pull Systems

Implementations vary

  • Visual / audio signal

  • “Chalk” square

  • One / two card Kanban

Material requirements planning jit

Material Requirements Planning / JIT

  • Stable Master Production Schedule

  • Flat bills of materials

  • Backflushing

  • Weekly MRP quantities with “call off” , a common approach

Jit purchasing

JIT Purchasing

  • JIT purchasing requires predictable (usually synchronised) demand

  • Single sourcing

  • Supplier quality certification

  • Point of use delivery

  • Family of parts sourcing

  • Frequent deliveries of small quantities

  • Propagate JIT down supply chain, suppliers need flexibility

  • Suppliers part of the process vs. adversarial relationships

Jit purchasing1

JIT Purchasing

  • Controls and reduces inventory

  • Reduces space

  • Reduces material handling

  • Reduces waste

  • Reduces obsolescence

Organisation for change

Organisation for Change

  • Multi-skilled team working

  • Quality Circles, Total Quality Management

  • Philosophy of joint commitment

  • Visible performance measurement

    • Statistical process control (SPC)

    • Team targets / performance measurement

  • Enforced problem solving

  • Continuous improvement

Total quality management tqm

Total Quality Management (TQM)

  • Focus on the customer and their requirements

  • Right first time

  • Competitive benchmarking

  • Minimisation of cost of quality

    • Prevention costs

    • Appraisal costs

    • Internal / external failure costs

    • Cost of exceeding customer requirements

  • Founded on the principle that people want to own problems

Jit flexibility

JIT Flexibility

  • Set-up time reduction

  • Small transfer batch sizes

  • Small lot sizes

  • Under capacity scheduling

  • Often labour is the variable resource

  • Smallest machine concept

Reducing uncertainty

Reducing Uncertainty

  • Total Preventative Maintenance (TPM) / Total Productive Maintenance

  • 100% quality

  • Quality is part of the process - it can’t be inspected in

  • Stable and uniform schedules

  • Supplier quality certification

Total preventative maintenance tpm

Total Preventative Maintenance (TPM)

  • Strategy to prevent equipment and facility downtime

  • Planned schedule of maintenance checks

  • Routine maintenance performed by the operator

  • Maintenance departments train workers, perform maintenance audits and undertake more complicated work

Implementation of jit

Implementation of JIT

Implementation of jit1

Implementation of JIT


1.Lower inventory levels

2.Identify problems

3.Eliminate problems

4.Improve use of resources

  • Inventory

  • People

  • Capital

  • Space

    5.Go back to step 1

Jit circle

JIT Circle


Design - focus


JIT Purchasing






Pull scheduling





Small machines

Jit limitations

JIT Limitations

  • Stable regular demand

  • Medium to high volume

  • Requires cultural change

  • Implementation costs

Computer aided production management systems capm

Computer Aided Production Management Systems (CAPM)



  • Vollmann T.E., Berry W.L. & Whybark D.C. (1992),”Manufacturing Planning and Control Systems (3rd Edition)”, Irwin, USA. ISBN 0-256-08808-X

    (Earlier editions just as good!)

  • Browne J., Harhen J, & Shivnan J. (1988),“Production Management Systems: A CIM Perspective”,Addison-Wesley, UK, ISBN 0-201-17820-6

Computer aided production management capm systems

Computer Aided Production Management (CAPM) Systems

“All computer aids supplied to the manager”

  • Specification - ensuring that the manufacturing task has been defined and instructions provided

  • Planning and control - scheduling, adjusting resource usage and priorities, controlling the production activity

  • Recording and reporting the status of production and performance

Computer aided production management capm systems1

Computer Aided Production Management (CAPM) Systems

Information systems responsible for:

  • Transaction processing - maintaining, updating and making available specifications, instructions and production records

  • Management information - for exercising judgements about the use of resources and customer priorities

  • Automated decision making - producing production decisions using algorithms

Capm systems

CAPM Systems

  • Planning

  • Control

  • Performance measurement

Planning modules

Planning Modules

  • Master Production Scheduling (MPS) - high level production plan in terms of quantity, timing and priority of planned production

  • Materials Requirements Planning (mrp) / Manufacturing Resources Planning (MRP)

  • Capacity Planning

Control modules

Control Modules

  • Inventory control - keeping raw material, work in process (WIP) and finished goods stocks at desired levels

  • Shop floor control (Production Activity Control) - transforming planning decisions into control commands for the production process

  • Vendor measurement - measuring vendors’ performance to contract, covering delivery, quality and price

Material requirements planning mrp

Material Requirements Planning (mrp)

“Material requirements plannning originated in the 1960s as a computerised approach for planning of materials acquisition for production. These early applications were based upon a bill of materials processor which converted demand for parent items into demand for component parts. This demand was compared with available inventory and scheduled receipts to plan order releases” Browne et al (1986)

Manufacturing resources planning mrp

Manufacturing Resources Planning (MRP)

  • The combination of planning and control modules was termed “closed loop MRP”. With the addition of financial modules an integrated approach to the management of resources was created. This was termed Manufacturing Resources Planning.

  • Material Requirements Planning (mrp / MRPI)

  • Manufacturing Resources Planning (MRP/MRPII)

Material requirements planning

Material Requirements Planning

  • Dependant demand

  • Time phased planning


  • Master Production Schedule

  • Bill of Materials

  • Inventory status


  • Infinite capacity

  • Fixed lead times

  • Fixed and predetermined product structure

Mrp record card

MRP Record Card

Mrp conventions

MRP Conventions

  • MRP time buckets

  • Scheduled receipts at start of period

  • Projected available balance at end of period

  • Planned order releases at the start of period

  • Planned orders vs. scheduled receipts

  • Number of buckets = planning horizon

Representation of product

Representation of Product

Linked mrp cards

Linked MRP Cards

Backwards scheduling

Backwards Scheduling

Forwards scheduling

Forwards Scheduling

Mrp domain

MRP Domain

  • Steady state systems

  • Low levels of uncertainty

  • Shallow / medium or deep product structure

  • Stable demand

  • Predominantly make to stock

  • Manufacturing orientation

Mrp parameters

MRP Parameters

  • Planning horizon

  • Size of time bucket

  • Lot sizing rules

  • Regeneration vs.. net change

Validity of mrp assumptions

Validity of MRP Assumptions

  • Infinite capacity vs. capacity planning

  • Fixed lead times / varying load

  • “Lead times are a result of the schedule”

  • Integration of planning levels requires feasibility at high and low levels

Typical control parameters

Typical Control Parameters

  • Safety stock

  • Safety lead time

  • Yield

  • Order quantity category

  • Min/max order levels

  • Max. days supply

  • Min. days between orders

Lot sizing

Lot sizing

  • Lot-for-lot

  • Economic Order Quantity (EOQ)

  • Complex optimisation algorithms

Uncertainties in mrp

Uncertainties in MRP

  • Environmental uncertainty

    • Customer orders

    • Suppliers

  • System uncertainty

    • Product quality

    • Scrap / rework

    • Process times

    • Design changes

  • MRP nervousness / instability

Dealing with uncertainty in mrp

Dealing with uncertainty in MRP

  • Safety stocks

  • Safety lead times

  • Safety due date

  • Hedging

  • Over-planning

  • Yield factors

Appropriate approaches

Appropriate approaches

  • Timing uncertainty: safety lead time

  • Quantity uncertainty: safety stock

Mrp nervousness

MRP Nervousness

  • Significant changes in plans due to minor changes in high level plans

  • Frequent changes in plans make the MRP system lose crdibility

Causes of nervousness

Causes of Nervousness

  • Demand uncertainty

  • Product structure characteristics

  • Incorrect lot-sizing rules

Nervousness solutions

Nervousness: Solutions

  • Stable MPS

  • Carefully change any parameter changes

  • Use different lot sizing rules at the high and low levels of the product structure

Mrp problems

MRP Problems

  • Quality of the model

  • Bill of materials structure

  • Non-material activities

  • Validity of the assumptions

  • Lack of 2 way time analysis

  • Quality of data

  • Regeneration / computational effort

  • Poor visibility

  • Operational aspects

How to implement mrp

How to implement MRP

  • Get accurate data

  • Make sure you have accurate data

  • Have good procedures to make sure that the data is always accurate

  • Remember approximately 75% of MRP implementations fail

  • Unsuccessful MRP costs nearly the same as successful MRP

Capacity planning

Capacity Planning



  • Vollmann T.E., Berry W.L. & Whybark D.C. (1992),”Manufacturing Planning and Control Systems (3rd Edition)”, Irwin, USA. ISBN 0-256-08808-X

  • Plossl G.W. & Wight O.W. (1973), “Capacity Planning and Control”, Production and Inventory Management, 3rd quarter 1973 pp31-67

Capacity planning1

Capacity Planning

“The function of establishing, measuring and adjusting limits or levels of capacity.

Capacity planning in this context is the process of determining how much labour and machine resources are required to accomplish the tasks of production.

Open shop orders and planned orders in the MRP system are input to CRP which “translates” these into hours of work, by work centre, by time period”

APICS Dictionary 1987

Capacity planning2

Capacity Planning

  • Plossl bath tub

  • Lead-time = queuing time + set-up time + processing time + transfer time

  • Queuing time is dependant upon the level of backlog in the system

  • Three reasons why queues go out of control

    • Inadequate capacity

    • Erratic input

    • Inflated lead time estimates

Plossl bath tub

Plossl Bath Tub

Lead time syndrome

Lead-time Syndrome

  • Vicious circle which can occur when queuing conditions change

  • Increased demand may increase backlog

  • Increased backlog increases demand

  • If the planned lead times are changed, more orders are likely to arrive to meet requirements during the increased lead time.

  • This further inflates lead times etc. etc.

Capacity control

Capacity Control

  • Input-output control: ensure that the demand never exceeds capacity

  • In MTO, backlogs act as buffers against workload variations. In this case it’s a trade off between maintaining resource utilisation and minimising lead-times and inventory

Capacity planning approaches

Capacity Planning Approaches

  • Infinite loading: assume infinite capacity, disregarding capacity constraints

  • Finite loading: work to capacity constraints

Infinite loading

Infinite Loading


Finite loading

Finite Loading

Infinite loading1

Infinite Loading

  • Easier - less computation required

  • Identifies and measures scheduled over and under loads

  • Shows how much capacity is required to meet the plan (finite loading does not)

Finite loading1

Finite Loading

  • Capacity of each resource specified in terms of “standard” and “maximum” capacity

  • Jobs loaded onto each work centre in priority order

  • When resources are “full”, jobs are rescheduled

  • Horizontal vs. vertical loading

  • The only way to revise a finite loading schedule is to start from scratch, rearranging jobs in a new priority sequence

Capacity planning3

Capacity Planning

“A prerequisite to having an effective capacity planning system is to have an effective priority planning system.

If the due dates, or lead times are incorrect, the schedule, the priorities and the projection of when the load will hit the resources will be fiction. The system will not work”

Plossl & Wight 1973

5 levels of capacity planning

5 Levels of Capacity Planning

  • Resource planning: highly aggregated, longest term level of capacity planning

  • Rough-cut capacity planning: uses MPS data

  • Capacity Requirements Planning (CRP)

  • Finite loading

  • Input / output control

Rough cut capacity planning

Rough-cut Capacity Planning

  • Capacity Planning Using Overall Factors (CPOF) calculates the overall direct labour requirements for the MPS and identifies load based upon historic data

  • Capacity Bills, uses BOM and planning data

  • Resource profiles, same as capacity bills, but time phased

  • See Vollmann et al for details

Capacity requirements planning

Capacity Requirements Planning

  • CRP utilises MRP information such as lot sizing and inventory data

  • Shop floor control provides information of the current status of items: only the capacity required to complete items is considered

  • CRP is based upon the infinite loading approach

Company classification

Company Classification



  • Woodward J. (1965), “Industrial Organisation: Theory and Practice”, Oxford University Press, England

  • New C.C. (1976), “Managing Manufacturing Operations”, British Institute of Management, Report No. 35.

  • Barber K.D. & Hollier R.H. (1986),”The Effects of Computer Aided Production Management Systems on Defined Company Types”, Int. J. Prod. Res. 24(2) pp311-327



  • Barber K.D. & Hollier R.H. (1986),”The Use of Numerical Taxonomy to Classify Companies According to Production Control Complexity”, Int. J. Prod. Res. 24(1) pp203-22

Manufacturing systems iii

Company Classification

  • Classification groups “like” items together

  • Dependent upon classification variables

  • Enables similarities and differences between companies to be identified

  • Identify appropriate planning & control method

  • Identify appropriate technology

Manufacturing systems iii

Classification Approaches

General company classification

  • Joan Woodward (1965) used Ministry of Labour categories for investigating organisational structure issues

  • Sector based classification commonly used by financial institutions (e.g. FT classification)

  • DTI - SMEs

    Classification of manufacturing

  • Mode of production e.g. Burbidge (1971), volume of production jobbing, batch, flow

  • Goldratt (1980) VAT analysis based upon pattern of material flow

  • Production control complexity New (1976), Barber & Hollier (1986)

Colin new classification

Colin New Classification

  • Survey of 186 companies to investigate manufacturing management practice

    Five classification areas:

  • Market - customer environment

    Relationship between cumulative lead time and delivery lead time e.g. make to stock or

    make to order

  • Product range and rate of product innovation

  • Product complexity - number of components per product, depth of product structure

  • Organisation of manufacturing system, functional vs. group layout

  • Cost structure of products

Market customer environment

Market / Customer Environment

  • Make to stock v/s make to order

  • Marucheck & McClelland (1986)

    Continuum from pure ETO - pure MTS

  • Positioning of company usually a strategic issue

  • Effects competitive factors - customisation vs. lead time and cost

  • Position effects inventory

  • Hicks (1994) Business process based description

Product complexity

Product Complexity

  • Depth of product structure

    effects co-ordination of assembly processes (phasing), uncertainties, lead times etc.

  • Number of components in product

  • Source of components (make / buy)

  • Standardisation / modular design vs. pure ETO

  • Concurrent engineering also increases control complexity

Organisational structure

Organisational Structure

  • Type of layout (process / cellular)

  • Management style

  • Company culture

  • Flexibility

Barber hollier 1986

Barber & Hollier (1986)

  • Worked aimed establish suitability of computer aided production management techniques for different types of company

  • Based upon production control complexity

  • Developed work of Colin New (1976)

  • Used numerical taxonomy to identify clusters of common companies

  • Work identified 6 groups of company

Chris voss 1987

Chris Voss (1987)

Modelling simulation

Modelling & Simulation



  • Kreutzer W. (1986), “System Simulation: Programming Languages and Styles”, Addison-Wesley

    ISBN 0-201-12914-0

  • Mitrani I (1982),”Simulation Techniques for Discrete Event Systems”, Cambridge University Press

    ISBN 0-521-23885-4



  • Systems identification

  • System representation

  • Model design

  • Model coding

  • Validation

    (last two points relate to simulation modelling)

Types of model

Types of Model

  • Iconic models: e.g. a globe is an iconic model of the earth

  • Analytical models: general solutions to families of problems based upon some strong theory (close form solutions)

  • Analytical models: represent systems through some abstract notion of similarity

  • Symbolic models: use of symbols to describe objects, relationships, actions and processes

    Churchman 1959

Manufacturing systems iii

  • Induction: “deducing a general principle from particular instances”

  • Deduction: “deducing a particular instance from a general law”

Descriptive model

Descriptive Model

“Descriptive models offer some symbolic representation of some problem space without any guidance on how to search it. The use of descriptive models is an inductive, experimental technique for exploring possible worlds”

Kreutzer 1986



“The term simulation is used to describe the exploration of a descriptive model under a chosen experimental frame”

Kreutzer 1986

“Simulation is partly art, partly science. The art is that of programming: a simulation should do what is intended. One should also know how to answer questions about the system being simulated”

Mitrani 1982

Limitations of simulation

Limitations of Simulation

  • Expensive in terms of manpower and computing

  • Often difficult to validate

  • Often yields sub-optimum results

  • Iterative problem solving technique

  • Collection, analysis and interpretation of results requires a good knowledge of probability and statistics

  • Difficult to convince others

  • Often a method of last resort

When to use simulation

When to use Simulation

  • The real system does not exist, or it is expensive, time consuming, hazardous or impossible to experiment with prototypes

  • Need to investigate past, present and future performance in compressed, or expanded time.

  • When mathematical modelling is impossible or they have no solutions

  • Satisfactory validation is possible

  • Expected accuracy meets requirements

Simulation methodology

Simulation Methodology

  • System identification

  • System Representation

  • Model design

  • Data collection and parameter estimation

  • Program design

  • Program implementation

  • Program verification

  • Model validation

  • Experimentation

  • Output analysis

Manufacturing systems iii

System Identification

“A system is defined as a collection of objects, their relationships and behaviour relevant to a set of purposes, characterising some relevant part of reality”

Kreutzer (1986)

Manufacturing systems iii

System Representation

“Symbolic images of objects, relationships and behaviour patterns are bound into structures as part of some larger framework of beliefs, background assumptions and theories of the problem solver”

Kreutzer 1986

Manufacturing systems iii

Model Design

“A model is an appropriate representation of some mini-world. Models can very quickly grow to form very complicated structures. Control and the constraint of complexity lie at the heart of any modelling activity. Care must be exercised to preserve only those chracteristics that are essential. This depends upon the purpose of the model”

Kreutzer 1986

Manufacturing systems iii

“It is necessary to abstract from the real system all those components (and their interactions that are considered to be important”

Mitrani 1982

Manufacturing systems iii

Model Coding

“This stage exists when computers are being used as the modelling medium. This stage seeks a formal representation of symbolic structures and their transformations into data structures and computational procedures in some programming language”

Kreutzer 1986

Types of simulation model

Types of Simulation Model

  • Monte Carlo

  • Quasi-continuous

  • Discrete event

  • Combined simulation

Monte carlo simulation

Monte Carlo Simulation

  • Derives name from roulette

  • Static simulation

  • Distribution sampling

  • No assumptions about model

  • Only statistical correlation between input and output explored

  • Results often summarised in frequency tables

  • Used for complex phenomena that are not well understood, or too complicated and expensive to produce other models

Quasi continuous simulation

Quasi- Continuous Simulation

“Dynamic simulation. The clock is sequenced by a clock in uniform fixed length intervals. The size of the increment determines the resolution of the model”

Kreutzer 1986

Discrete event simulation

Discrete Event Simulation

  • Asynchronous clock

  • Assumes nothing interesting happens between events

  • Queuing networks in which the effects of capacity limitations and routing strategies often studied using DES

  • This type of simulation most frequently used for simulating manufacturing systems

Types of discrete event simulation

Types of Discrete Event Simulation

  • Event scheduling

  • Process interaction

  • Object orientated

  • Activity scanning

Event scheduling approach

Event Scheduling Approach

  • Event scheduling binds actions associated with individual events into event routines.

  • The monitor selects event for execution, processing a time ordered agenda event notices.

  • Event notices contain a time and a reference to an event routine.

  • Each event can schedule another event, which is placed in the correct position of the agenda.

  • The clock is always set to the time of the next immanent event”

Process interaction approach

Process Interaction Approach

  • Focuses on the flow of entities through the model

  • Views system as concurrent, interacting processes

  • Life cycle for each class of entities

  • Monitor uses agenda to keep track of pending tasks

  • Monitor records activation times, process identities and state that the process was last suspended

Object orientated programming

Object Orientated Programming

  • Process records the values of all local variables

  • Object contains, attributes (data), activities (processes) and lifecycle

  • Communication between objects only through well defined interfaces provided by messages which an object is programmed to respond to

  • Classes / sub classes

  • Instances

  • Inheritance

Activity scanning approach

Activity Scanning Approach

  • Each event is specified in terms of the conditions that need to apply for the event to start and finish

  • Each event has a set of actions that take place when it finishes

  • Model execution is cyclic, scanning all activities in the model testing which can start / finish.

  • Clock only moves when whole cycle leaves status unchanged

  • 3 phase structure computationally expensive

  • “Conditional Sequencing” since programmer only states start and end conditions

Types of simulation

Types of Simulation

  • Deterministic - no random component

  • Stochastic - represents uncertainties

Stochastic simulation

Stochastic Simulation

  • Sampling experiments

  • Standard statistical approaches such as design of experiments used

  • Random processes based upon pseudo random number generators

Pseudo random number generators

Pseudo-Random Number Generators

  • Seed based: algorithm produces “random” number from seed. Repeated execution gives same streams of random numbers

  • Non-seed based, random number generated using time, or status of computer



Model qualification














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