Week 3 - Supply Chain Modelling Flashcards

1
Q

What is a model

A

Is intended to represent a real system, either existing or planned

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2
Q

What are the major advantages of a model? (2)

A

• It succinctly represents the real system
• When investigated you are able to discover things about the real system

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3
Q

What is a system and it’s function? (2)

A

• Is a collection of interrelated components that work together towards a collective goal
• the function is to receive inputs and transform these into outputs

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4
Q

Name 3 characteristics of systems

A

• Environment
• Organisation
• Interdependency

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5
Q

Explain environment as a characteristic of systems

A

Systems are contained within an environment that contains other systems and external agencies and the scope of a system is defined by its boundary

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6
Q

Explain organisation as a characteristic of systems

A

The components of a system work towards a collective goal known as the system’s objective

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7
Q

Explain interdependency as a characteristic of a system

A

Systems are made up of subsystems (components) that may themselves being made up of other subsystems thus parts of a system are dependent on one another in some way

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8
Q

What is combinatorial complexity?

A

Is when we have activities that have a 2 way relationship with every other activity

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9
Q

How can the number of interconnections in combinatorial complexity be calculated?

A

n(n-1) where n is the number of activities

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10
Q

What is dynamic complexity?

A

Can arise in systems due to feedback and delays for example between cause and effect

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11
Q

What are the 2 main modelling methods?

A

• Descriptive modelling
• Explanatory modelling

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12
Q

What is descriptive modelling? (2)

A

• Based on measuring observed behaviour
• If a system shows a certain regularity in behaviour then future behaviour may be predicted under the same conditions

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13
Q

Name some examples of descriptive modelling (3)

A

• Regression analysis
• Data mining
• Machine learning

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14
Q

What is explanatory modelling? (2)

A

• is based on a systems view and represents the real system structure
• It emphasises on the identification on the processes that are decisive for system behaviour

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15
Q

What is a deterministic model?

A

Is a model that does not represent uncertainty and so for a given set of conditions and parameters will always produce the same outcome

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16
Q

What does a deterministic model imply?

A

It implies that given a well enough detailed snapshot of a system we should be able to forecast the system’s dynamic behaviour perfectly thus are able to be analytically traceable and expressed as a mathematical formulae

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17
Q

What does a stochastic model include? (2)

A

Includes some random component such as:
• variable demand rate
• variation or processing rates due to natural variability

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18
Q

Benefit and drawback of stochastic models

A

• Models have an increased realism (benefit)
• (Drawback) make even simple models intractable

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19
Q

3 Examples of static models

A

• Linear programming
• Spreadsheets
• Monte Carlo simulation

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20
Q

How should models be developed? (According to Pidd 2009 applying the principles of Occam’s razor 1300)

A

Developed so that they are as simple as possible and yet are valid and useful for their intended purpose

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21
Q

What are the general principles for model development? (4) (Robinson van der zee 2018)

A

• Focus on the decision, not the system
• Abstract - do not model all you know about the world
• The model should drive the data requirements and not the available data drive the model
• start small and add

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22
Q

What is required when starting a simple model? (Brooks and Tobias 2000)

A

Requires us to define a number of simplifications to define what simple model

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23
Q

What is a puzzle? (Pidd 2009)

A

Is a set of circumstances in which there is no ambiguity whatsoever once so,e thought has been given to what is happening or needs to be done

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24
Q

What are the issues that need to be faced with puzzles? (3)

A

• entirely clear
• the range of options being completely known
• a single correct solution

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25
Q

What is a problem?

A

Has no single answer but has several equally valid solutions

26
Q

What are messes? (2)

A

• Is a set of circumstances which there is extreme ambiguity and in which there may well be disagreement
• There is a system of problems with multiple stakeholders with differing views

27
Q

What are the six principles of modelling? (Michael Pidd in ‘tools for thinking’)

A

• Model simple, think complicated
• Be parsimonious, start simple and add
• Divide and conquer, avoid mega-models
• Use metaphors, analogies and similarities
• Do not fall in love with the data
• Model-building may feel like muddling through

28
Q

What does ‘divide and conquer, avoid mega-models’ mean?

A

Means breaking large general-purpose models down into simple models in order to better validate, interpret and explain

29
Q

What does ‘use metaphores, analogies and similarities’ mean? (4)

A

Means getting a variety of perspectives of a problem such as:
• Personal
• Direct - think of parallel situations from real life
• fantasy - as the question ‘just suppose…’

30
Q

What does ‘do not fall in love with data’ mean?

A

Means data collection should be based around the modelling and only being collected in 3 types which are contextual, realisation and validation

31
Q

What is meant by a soft approach to modelling?

A

Concerned with problem structuring when it’s necessary to understand context and consider people’s opinions

32
Q

What is the impact of problem structuring in terms of a soft approach to modelling? (2)

A

• Can enable people to make better decisions
• Could prelude to more formal mathematical modelling approaches

33
Q

Characteristics of soft approaches (4)

A

• Assume problem is not straight forward
• Don’t assume organisations are just perfect intern of human labour functions and objectives
• Has the idea that models are developed to help people to think through their own positions and engage in debate with other about possible actions
• Stress the importance of organisational and individual learning

34
Q

Name 2 soft approaches to modelling

A

• Soft systems methodology
• System dynamics

35
Q

What is soft systems methodology?

A

Is a way of using system ideas with human organisations to help humans make changes and understand their effects

36
Q

What is soft systems methodology method?

A

Move from an unstructured problem situation to a problem situation that is expressed with the purpose to uncover different perceptions of why the intervention is needed and what it is that appears to go on

37
Q

What is needed to be understand in soft systems methodology (method) (3)

A

• Structure - static aspects such as physical layout, power hierarchies and formal informal communication systems
• Process - how things are done and what people are trying to do
• Climate - the culture of the organisation

38
Q

The six components of a root definition

A

• Customers
• Actors - human who carry out activities in a system
• Transformation process - conversion from input to output
• Weltanschauung - the world wide view that makes the root definition
• Ownership - the individuals responsible for the system
• Environmental constraints - such as legal, physical or ethical

39
Q

What are root definitions used for? (2)

A

• To develop a conceptual model showing the interconnections of the activities that must be present for the root definition to make sense
• The conceptual model is then compare to the current situation to see what changes need to be made

40
Q

What is system dynamics?

A

Provides a way of viewing human systems by stressing the importance of certain structural features such as feedback control

41
Q

What are casual loop diagrams used for?

A

To understand the broad structure of a system and the elements are linked by arrows which indicate the direction of causality of the link

42
Q

What does a casual loop diagram/system archetype represent and the benefit of this?

A

A template of common behaviours in systems which provides a way of understanding the underlying dynamics to explain behaviour

43
Q

What do system dynamics models involve?

A

The construction of a dynamic simulation model where the stocks of variables are connected together via flows

44
Q

What computer software can implement SD simulation model? (3)

A

• Stella ll
• Vensim
• iThink

45
Q

Name 3 hard modelling approaches

A

• Linear programming
• Simulation modelling
• Heuristic search

46
Q

What are the set of assumptions for linear programming?

A

• a set of alternative courses of action
• Knowledge and information that permit the prediction of the consequences of choosing any alternative
• a criteria for determining which set of consequences is preferred

47
Q

Name the two types of simulations in simulation modelling?

A

• Static simulations
• Dynamic simulations

48
Q

What are static simulations?

A

Are simulations that are not concerned with dynamics interactions through time and include monte Carlo simulation

49
Q

What are dynamic simulations?

A

Are simulations that are concerned with systems whose behaviour varies through time and include system dynamics, discrete event simulation and agent-based simulation

50
Q

Characteristics of systems best suited to the use of dynamic simulation (3)

A

• Dynamic
• Interactive - system consists of a number of components that interacts and produces distinct behaviour of the system
• Complicated

51
Q

What is a heuristic search? (2)

A

• Is similar in nature to simulations in terms of there being no guarantee that any proposed solution will be optimum
• Provide ways of automatically generating solutions to problems that have been formulated in certain ways

52
Q

What do heuristic search approaches include? (3)

A

• Tabu search
• Simulated annealing
• Genetic algorithms

53
Q

What is a tabu search?

A

Rets on the procedures that declare certain search moves to be forbidden and in a heuristic search it will normally choose the lowest p-cost no-tabu neighbour

54
Q

What is simulated annealing?

A

Is simulated annealing the algorithms try to avoid convergence on local optima by careful control

55
Q

What are genetic algorithms?

A

Are from population genetics with the notion that circumstances temper random mutation by selecting some mutations as better suited to survival than others

56
Q

Where can soft systems methodology be applied? (4)

A

• cost drivers of maintenance operations
• Supply chain design
• Coordination in the supply chain
• Contracting in the supply chain

57
Q

Where can system dynamics be applied? (5)

A

• Supply chain design
• Resilience to disruptive events
• Sustainability in the supply chain
• Impact of mitigation policies in a pandemic
• Impact of risks in the transportation system

58
Q

Where can linear programming be applied? (3)

A

• Supply network design
• Scheduling
• Vehicle routing

59
Q

Where can simulation modelling be applied? (5)

A

• Supply chain performance (SCOR)
• Capacity planning
• ‘last mile’ logistics
• Food retail distribution
• End-of-life reverse supply chain for electric vehicle batteries

60
Q

Where can a heuristic search be applied? (5)

A

• Facility location
• Production time crashing
• Inventory routing
• Logistics route optimisation
• Lot sizing