The GRAI method Part 2: detailed modelling and methodological issues

B. Vallespir, G. Doumeingts

The GRAI method, Part 2: detailed modelling and methodological issues

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Content

• • • • •

1. 2. 3. 4. 5.

Introduction The GRAI nets The structured approach The rules of inconsistencies The GRAI methodology

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First part

INTRODUCTION

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Definition of the GRAI method

• The GRAI method owns to the enterprise modelling domain. The purpose is to design or reengineer production systems (manufacturing or service). • The GRAI method focuses on the decisional aspect (control system). • From a general point of view, the GRAI method applies to performance improvement.

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Composition of the GRAI method The GRAI Method: • is built up starting from a reference model, the GRAI model, which is a consistent set of concepts that model any production system in a generic way and a priori, • is based on graphical modelling languages which instantiate the concepts of the GRAI model to build the specific model of the studied case, • follows a structured and participative approach within which actors and steps are defined, allowing effectiveness and time saving. The GRAI method, Part 2: detailed modelling and methodological issues

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Composition of the GRAI method

Note: The GRAI reference model and the GRAI grid are not presented in this course and can be found in: The GRAI Method Part 1: global modelling

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Application domains of the GRAI method • Production systems engineering, • Choice and implementation of software packages for management: ERP (Enterprise Resources Planning), SCM (Supply Chain Management), CRM (Customer Relationship Management) or other computerized solutions (decisional...); • Choice and implementation of performance indicators systems; • Development and implementation of industrial strategies; • Support to quality approaches; • Knowledge Management.

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Application domains of the GRAI method

Remark: The GRAI method takes part in these applications without being sufficient enough in general ⇒ necessity to increase the modelling domain (see GRAI methodology, 5th part)

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Second part

THE GRAI NETS

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INTRODUCTION

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Definition

The GRAI Nets represent the running of the whole or a part of a decision centre according to the GRAI modelling concepts (model of a decision centre activities).

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Situation of GRAI nets in modelling F1

F2

F3

...

Fn

H/P H/P H/P

Principle: There is only one network by decision centre

1

Urgent order

MRP

Workload over 3 months

To centre the plan over 3 months

2

PL/30

MR/10

Workload over 3 months completed

To complete workload

Objective: Respect of delivery dates

Progress report on the production DV

Practically: Sometimes several (size, version, etc.)

PL/30 TO PLAN

Rules Priorities Requirement origin MT Workload

PL/30

H = 3 months P = 1 day

To plan workload + ST schedule #

• Delivered quantity • Int resour.

3 To adjust load (smoothing)

Workload for MT

PL/30

Methodological information

PL/20 PL/30

Man. order unreach able

Load distributed per period and station

The GRAI method, Part 2: detailed modelling and methodological issues

PL/10

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Graphical representation of an activity

Support

Trigger

#

Activity

Result

Support

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MODELLING COMPONENTS

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Activity and entity Activity. Part of the behaviour of a decisionmaking centre. An activity is dynamic and provides one or more entities. The activities are named and numbered.

Name

Name

Entity. Physical or abstract object that belongs to the control system. The entities are necessary to the course of the activities or are produced by those ones. The entities are named.

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Activities type Two types of activities exist Decision activity Execution activity

Trigger

# Support Support

Trigger

# To execute

Support

Result

T o d e c i d e

Support

Result

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Activities type Execution. Deterministic activity. Activity giving the same value to the result for the same values of the convergent entities (trigger and supports). Example: activity managed completely by a rule, procedure, programme, etc. Decision. Activity being able to give several values to the result for the same values of the convergent entities. Example: choice of a solution in uncertain context The GRAI method, Part 2: detailed modelling and methodological issues

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Nature of entity There are seven natures of entities: • Objective. Level of performance attended after the realization of the activity. • Decision variables. Element on which one can play during the activity implementation. • Criterion. Help to the choice of the actions on the decisions variables. • Rules. Specification of the behaviour of an activity or a part of this one.

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Nature of entity There are seven natures of entities (cont’): • Performance indicator. Report on a performance. • Information. Entity of informational nature unspecified. • Resource. Concrete means, technical or human, necessary to the implementation of the activity. The nature of the entity is mentioned (or be an information by default) Rule

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Role of entity Three roles are possible for an entity Support. Entity required for the progress of an activity Result. Entity produced by an activity Trigger. Entity required for the progress of an activity and of which the disposal triggers the activity.

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Additional information Trigger • The trigger of an activity can also consist of an exogenous logical condition. In this case, this one is indicated as an entity trigger. • The trigger can also consist in the period of the level where the decision centre is located. In this case, no trigger is mentioned. Support • Objectives, decision variables and criteria are only and mandatory represented for decisional activities. The GRAI method, Part 2: detailed modelling and methodological issues

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Reference operators Reference operators are used when it is necessary to indicate the origin or the destination of an entity when this origin or this destination is external with the diagram. Situations for which these operators are necessary: • when an entity circulates between the studied system and its environment, • when an entity circulates from one decision centre to another one, • when the net is too large to enter on a page! The GRAI method, Part 2: detailed modelling and methodological issues

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Reference operators

Origin : Destination :

R/A

Entity

Entity

R/A

• R: number of the net, • A: number of the origin or destination activity • R/A: name of the system or service out of the study domain The GRAI method, Part 2: detailed modelling and methodological issues

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LOGICAL OPERATORS

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Generalities • It appears combinations or decompositions in the GRAI nets which result in divergences and convergences into AND and OR, from entities to activities and reciprocally. These situations are represented by logical operators. • The representation of these operators follows the general rule: • AND are represented by double features (| |) • OR are represented by simple features (|)

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Generalities Example OR Convergence

AND Divergence

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Particular case Link: Entity → Activity / AND / convergent

= Because supports are not optional

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Prohibited structure Link: Entity → Activity / OR / divergent Entity Entity

⇒

C h o i c e X X

The outcome of the entity to one or the other of the activities supposes the idea of a choice: this implies to clarify this choice The GRAI method, Part 2: detailed modelling and methodological issues

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Prohibited structure Link: Activity → Entity / AND / convergent

An activity must have its own result Link: Activity → Entity / OR / convergent

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EXAMPLE OF NETS

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Example

1

MRP

Workload over 3 months

To centre the plan over 3 months

Urgent orders

2

PL/30

MR/10

Workload over 3 months completed

to complete workload

Objective: Respect of delivery dates

Progress report on the production DV • Delivered quantity • Int resour.

PL/30 H = 3 months P = 1 day

TO PLAN

#

To plan workload + ST schedule

3 To adjust load (smoothing)

Workload for MT

PL/30

Rules Priorities Requirement origin MT Workload

PL/30

PL/20 PL/30

Methodological information

Man. order unreachable

Load distributed per period and station

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PL/10

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Link with the corresponding grid Example of a control grid

50

2 years 1 month

40

8 months 1 month

Forecasts of sales per families

To manage products

To plan

To manage resources

To make Long Term plan

• To define engagement strategy • To define structural S/C

To man. purchase To man. procurem. • To look for suppliers • To negotiate markets

• To define proc. strategy • To define critical proc.

Consolidated orders

Internal information

MSP MRP

To make proc. plan

To plan workload + MT schedule

To define conjectural S/C

To plan workload + ST schedule

To assign the personnel

Orders book

30

6 month 1 week

To send orders to suppliers

20

3 months 1 day

To recall suppliers

10

1 day RT

To define conjectural S/C

To define proc. parameters

Urgent orders To dispatch To record orders

Inventories level

Example

To record I/O raw materials, materials and FP

Workload for MT

PL/30

Title

Date

76

1

MRP

Workload over 3 months

To centre the plan over 3 months

Urgent order

2

Objective: Respect of delivery dates

PL/30

H = 3 months P = 1 day

TO PLAN

MR/10

#

PL/20

Methodological information

Progress report on the production DV • Delivered quantity • Int resour.

PL/30 TO PLAN

To plan workload + ST schedule

Workload over 3 months completed

to complete workload

#

To plan workload + ST schedule

H = 3 months P = 1 day

Rules Priorities Requirement origin MT Workload

PL/30

PL/20 PL/30

Methodological information

Date

3 To adjust load (smoothing)

External information

Man. order unreachable

Load distributed per period and station

Title

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PL/10

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Example: links with the corresponding grid

1

MRP

Workload over 3 months

To centre the plan over 3 months

Urgent order

2

PL/30

PL/40

MR/10

MRP

Workload over 3 months completed

to complete workload

Objective: Respect of delivery dates

Progress report on the production DV

To plan workload + MT schedule PL/30

To recall suppliers GP/20

Inventories level

PL/30

Rules Priorities Requirement origin MT Workload

PL/30

To assign the personnel

To plan workload + ST schedule PL/20 PL/10 To dispatch

• Delivered quantity • Int resour.

3 To adjust load (smoothing)

MT Workload

PL/30

GR/20

PL/30

Man. order unreachable

Load distributed per period and station

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PL/10

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Example: links with the corresponding grid Consistence GR/10

To recall suppliers GP/20

Absent of the grid: normal (additional detail at the level of the nets)

Progress report of the production

To plan workload + ST schedule PL/20

To assign the personnel GR/20

Absent relations in the net: abnormal

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Example: links with the corresponding grid Analysis of the content of the decision framework PL/30 → PL/20 PL/30

In the grid: To plan workload + MT schedule PL/30

To plan workload + ST schedule

Objective Respect of the delivery date DV

Transmission of the value of the objective

PL/30

• delivered quantity • Int resour.

Transmission of the value of the constraints

PL/30

MT Workload

Order transmission

PL/30

Man. order unreachable

PL/20

Information follow up

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Third part

THE STRUCTURED APPROACH

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General principles

Models

OBJECTIVES

Analysis

Design

Implementation Real world

Modelling

?

Existing system (As-is)

Target system (To-be)

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The actors BOARD GROUP

is & Analys on i validat

Define the objectives and the domain of the study Evaluate and validate the results

Synthesis group (Main deciders)

GRAI Specialists (sensors)

Perform the study als Propos Definition Valida Proposals Analysis & tion validation Support the study Inform ation Va Working lid ati groups on Inf Interviewees orm Look for ati on solutions Provide information

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The actors Example of a group composition (study of a SME)

• • • • • •

Board group person in charge of the SME responsible for the division of the group to which the SME is attached Synthesis group person in charge of the SME responsible for procurement / subcontracting responsible for manufacturing …/… The GRAI method, Part 2: detailed modelling and methodological issues

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The actors Example of a group composition • • • •

responsible for quality responsible for estimation / preparation responsible for scheduling responsible for commercial Specialists • a specialist from a service company • a specialist assistance provided by the group

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General progress Initialisation Initialisation Modelling Modelling and and existing existinganalysis analysis

Context Context and andobjectives objectives of ofthe thefuture futuresystem system

Design Designof ofthe the future futuresystem system Actions Actions plan plan The GRAI method, Part 2: detailed modelling and methodological issues

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Course of the phase « initialisation » Presentation Presentationof ofthe the study study phases phases Synthesis group Board Group Groups Groups definition definition

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Course of the phase «modelling and existing analysis» Global Globalmodelling modelling

Detailed Detailedmodelling modelling

Analysis Analysis assessment assessment

• Grid • Interviews planning

• Interviews • Setting form (realisation of the nets) • Review of the grid

• Determination of the inconsistencies • Analysis report

Synthesis group

Interviewees

Synthesis group

Synthesis group Board group

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Course of the phase « context and future system objectives » Definition Definitionof ofthe the external externalconstraints constraints

Synthesis group

Definition Definitionof ofthe the internal internalconstraints constraints

Synthesis group

Description Description of ofobjectives objectives of ofthe thefuture futuresystem system

Synthesis group Board group

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Course of the phase « future system design » Design Designinitialisation initialisation

Global Globaldesign design

Detailed Detaileddesign design

• Inconsistencies solving • Proposals for orientations • Choice of one orientation

Synthesis group Board group

• Grid • Global nets

Synthesis group

• Detailed nets

Working groups

Working groups

Synthesis group

Design Designsynthesis synthesis

• Design report Board group

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Some precisions

• The phases do not proceed a such sequential way (overlapping, looping); • It is necessary to regularly gather the group of synthesis (to remain "in catch" with the study) without overloading its members (1/2 day every 2 or 3 weeks): that involves intermediate versions of the results.

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Example of planning

The actors

Modelling / Diagnosis 3/4 months maximum

Design 3/4 months maximum

Board Group Synthesis Group Interviews Working Groups

Double arrow = Framework

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Fourth part

THE INCONSISTENCIES RULES

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Generalities about inconsistencies rules • The most important rules come from the GRAI model (in this way, they are a part of the model); • The inconsistencies rules correspond to the ideal vision of a control system; • The goal is not to obtain such an ideal system, the studied system will not be requested to match all the rules:

⇒ Set of inconsistencies rules = Guide to think about the consistence of the studied system. The GRAI method, Part 2: detailed modelling and methodological issues

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«A» rule Horizons must be sliding. Non-sliding horizon

Sliding horizon Planning built at t = 0 Planning built at t = P Planning built at t = 2P Planning built at t = 3P Planning built at t = H

0

P

2P

Revision

3P

4P =H

H+P

0

P

2P

3P

4P =H

H+P

New forecast

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«A» rule Vision of the future Non-sliding horizon

Sliding horizon

4P = H 3P = H-P 2P P 0 0

P

2P

3P

4P =H

H+P

0

P

2P

3P

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4P =H

H+P

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«A» rule The control systems we take into account are based on forecasts (that is why the notion of horizon exists); The only way to permanently keep a minimal vision of the future is to have a sliding horizon; With a sliding horizon: Vision at decision period = H, Minimal vision = H - P; Note: when H = P, the notion of sliding horizon has no sense anymore and we consider then that the situation corresponds to a non-sliding horizon. The GRAI method, Part 2: detailed modelling and methodological issues

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«B» rule The horizon must be longer than the time to achieve physical activities of production controlled by the decision centres of the level. L = delivery date Decision Decision The planning realized at L-d centre centre must take the result expected at L into account, then a T= Controlled vision in the future over d is Controlled T = necessary: L activity L-d activity ⇒H≥d Duration = d Note : This is true when there is a commitment about the delivery date (generally the case in production management). The GRAI method, Part 2: detailed modelling and methodological issues

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« B » rule Definition of the relationships between physical activities of production and decision centres Knowledge coming up from production management

Master Production Schedule

Horizon ≥ D

Load planning

Horizon ≥ d

Production Purchasing

Manufacturing d

D

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« B » rule Precision The former general rule is true for the nominal running since the vision in the future is equal to H at the period of decision making. In the case where many adjustments are needed, the minimal vision in the future must be considered: H - P. Then, if the environment of the system is very disturbed, it is necessary that: H-P≥d The GRAI method, Part 2: detailed modelling and methodological issues

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«C» rule

Ma S na tab ge ilit me y a nt nd lig htn e

ss ne ve

Stability: by implementing « enough » a plan before revising it. Management lightness: less effort with a batch-process of events.

ti ac Re

• Shorter the period is, more the system is reactive, • Longer the period is, more the system is stable and light to manage.

ss

The value of the period is linked to the frequency of fluctuations impacting the decision centre considered.

Value of the frequency

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«D» rule The ideal number of decisional levels is between three and five. Too much levels make the system too complex and is often the symptom of a synchronization issue between decision centres. Not enough levels does not allow a « progressive coordination » of the system. Empirical rule defined by experience. The GRAI method, Part 2: detailed modelling and methodological issues

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«E» rule The horizon of a level must have a value equal or greater than the value of the period of the upper level. Sources of variations: Decision framework

Order

Decision centre

Follow -up

Orders and follow-up are continuously received, the decision framework is emitted only at each period of the upper level. Then, the environment of the decision centre is stable from this point of view during Pn+1 (period of the upper level). This stability is taken into account by having: Hn ≥ Pn+1 Empirical rule : Hn = 2.Pn+1

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«F» rule A decision framework must not jump a level. Configuration that does not match the rule:

• This configuration denies the raison d’être of the jumped decision centre and the interest for having a progressive co-ordination. • The decision centre receptor receives a frame not often enough and too global related to the detail it processes itself.

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«G» rule A decision centre must receive only one decision framework. • The objectives sent risk to be contradictory; • The decision space of the decision centre receptor corresponds to the intersection of decision spaces defined by each decision framework (decision variables and constraints). This space risks to be empty.

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« G » rule Decision framework

Configuration that does not match the rule:

Decision framework

Decision centre

Configuration theoretically possible (mainly if it exists a unique decision centre upstream the decision frameworks) but not practically recommended.

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«H» rule A decision framework inter-functions is possible only if the decision centre emitter belongs to a function whose the basic elements contain the basic elements of the function that the decision centre receptor belongs to. Reminder:

Activity control Production activity control: basic concepts Activity Activity management management Product Product management management PxT

PxRxT Resource Resource management management

Product Product

Activity Activity

Product Product

RxT

PxR P

Resource Resource R Date

«Activities management» ? «Planning»

Title

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« H » rule Example of forbidden configuration: To manage To plan products

The decision centre emitter does not master the notion of Resource: it cannot completely frame a decision centre belonging to the “Plan” function

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« H » rule

Possible configurations (for the three elementary control functions):

Theoretically possible configuration but forbidden by the G rule:

To manage products

To manage products

To plan

To manage resources

To plan

To manage resources

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«I» rule A function is an exclusive set of activities having a role participating to a common and identified finality. • Common understanding of the function and its finality, • Each decision centre of the function participates effectively to the finality of the function, • Consistent set of objectives deployed all along the hierarchy.

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«J» rule Each elementary control function must have a decision centre at each hierarchical level. Reminder: Activity control Production activity control: basic concepts Activity Activity management management Product Product management management PxT

PxRxT Resource Resource management management

Product Product

Activity Activity

Product Product

RxT

PxR P

Resource Resource R Date

Title

«Activities management» ? «Planning» 26

The «Activity management (planning) / Products management / Resources management» triplet cannot be dissociated ⇒ If one element of the triplet is present at one level, then the two other ones must be present as well.

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«K» rule The production management system must be informed enough about its environment (external information) and about the physical system (internal information). The system is: • open: information coming from its environment, • looped : information coming from the physical system. Knowledge about production management is necessary to know what information is required and where. The GRAI method, Part 2: detailed modelling and methodological issues

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Conclusions about inconsistencies rules • Some rules are general and express control principles (GRAI model): they are applied to the grid (rules presented here); • Other more accurate rules come from production management principles and are applicable to the grid and to the nets (rules not presented here); • It is possible to enrich this set of rules (with rules dedicated to a class of systems, etc.). The GRAI method, Part 2: detailed modelling and methodological issues

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Fifth

THE GRAI part METHODOLOGY

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The GRAI methodology: definition • The GRAI Methodology applies in the same general optics as the GRAI method (improvement of performances). • The GRAI Methodology is also based on a reference model, graphic languages and a structured approach. • The difference concerns: • the modelling domain, • the offer of specific approaches according to the aims of the study. The GRAI method, Part 2: detailed modelling and methodological issues

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Modelling domain (by sub-systems) Entity/Relationship or class diagram

functions

entity

relation cardinality entity

DECISIONAL SYSTEM

H/P

INFORMATION SYSTEM PHYSICAL SYSTEM

trigger

support

activity

entity

GRAI Grid

support

result

control activity support

control activity

GRAI nets

support

Actigrams The GRAI method, Part 2: detailed modelling and methodological issues

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Modelling domain: global representation Actigram control

FUNCTIONAL VIEW

activity

control

support

activity support

DECISIONAL SYSTEM INFORMATION SYSTEM control

extended activity resources

logical operator process

PHYSICAL SYSTEM

PROCESS VIEW

extended Activity

resources

Extended Actigram The GRAI method, Part 2: detailed modelling and methodological issues

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The offer of specific approaches CHOICE AND IMPLEMENTATION OF IT/TECHNICAL/ORGANISATIONAL SOLUTIONS GIMSOFT Choice of IT solutions

PROGRAI

INDUSTRIAL SYSTEMS ENGINEERING

PERFORMANCE MANAGEMENT

GIMPLANT Implementation of solutions

Enterprise process improvement

ECOGRAI

INDUSTRIAL STRATEGY

Performance indicators

BENCHGRAI Benchmarking

GEM

Evolution management enterprise

GRAI Engineering

Product design control

GIM Audit GIM

Enterprise modelling

GRAI Model

Languages

GRAI Message Manufacturing Strategic Plan

GRAI Quality GRAI Knowledge

KNOWLEDGE MANAGEMENT

Generic approach

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Specific approaches and life cycle Evolution control oriented

SIS oriented

Definition of objectives and strategic planning

GRAI KNOWLEDGE

GEM

GRAI QUALITY

GRAI MESSAGE

GIM PLANT

Implementation of technical solutions ECO GRAI

Exploitation/follow up of implemented system

BENCHGRAI

GIM SOFT

Choice/development of technical solutions

GRAI ENGINEERING

Target system design

GIM

Diagnostic

GIM AUDIT

Modelling of the existing

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Thank you for your attention

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