The GRAI method Part 2: detailed modelling and methodological issues

Transcription

1 The GRAI method Part 2: detailed modelling and methodological issues B. Vallespir, G. Doumeingts 1

2 Content 1. Introduction 2. The GRAI nets 3. The structured approach 4. The rules of inconsistencies 5. The GRAI methodology 2

3 First part INTRO- DUCTION 3

4 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. 4

5 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. 5

6 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 6

7 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. 7

8 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, 5 th part) 8

9 Second THE GRAI part NETS 9

10 INTRODUCTION 10

11 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). 11

12 Situation of GRAI nets in modelling F 1 F 2 F 3... F n H/P H/P H/P PL/30 Workload for MT MRP Urgent order Principle: There is only one network by decision centre Practically: Sometimes several (size, version, etc.) # 1 TO PLAN To plan workload + ST schedule To centre the plan over 3 months Methodological information H = 3 months P = 1 day PL/20 MR/10 Workload over 3 months 2 PL/30 Progress report on the production PL/30 To complete workload PL/30 Objective: Respect of delivery dates DV Delivered quantity Int resour. Man. order unreach able Workload over 3 months completed 3 To adjust load (smoothing) Load distributed per period and station Rules Priorities Requirement origin MT Workload PL/10 PL/30 12

13 Graphical representation of an activity Support Trigger # Activity Result Support 13

14 MODELLING COMPONENTS 14

15 Activity and entity Name 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 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. 15

16 Activities type Two types of activities exist Execution activity Decision activity Trigger # Support Support T o d e ci Support Trigger # To execute Result d e Support Result 16

17 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 17

18 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. 18

19 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 19

20 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. 20

21 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. 21

22 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! 22

23 Reference operators Origin : R/A Entity Destination : 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 23

24 LOGICAL OPERATORS 24

25 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 ( ) 25

26 Generalities Example OR Convergence AND Divergence 26

27 Particular case Link: Entity Activity / AND / convergent = Because supports are not optional 27

28 Prohibited structure Link: Entity Activity / OR / divergent Entity Entity C h o i c e 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 X 28

29 Prohibited structure Link: Activity Entity / AND / convergent Link: Activity Entity / OR / convergent An activity must have its own result 29

30 EXAMPLE OF NETS 30

31 Example PL/30 Workload for MT MRP Urgent orders 1 To centre the plan over 3 months Workload over 3 months 2 to complete workload Workload over 3 months completed TO PLAN MR/10 H = 3 months P = 1 day PL/30 Progress report on the production PL/30 Objective: Respect of delivery dates DV Delivered quantity Int resour. 3 To adjust load (smoothing) Rules Priorities Requirement origin MT Workload PL/30 # To plan workload + ST schedule PL/20 Methodological information PL/30 Man. order unreachable Load distributed per period and station PL/10 31

32 Link with the corresponding grid Example of a control grid External information To manage products To man. purchase To man. procurem. To plan To manage resources Internal information 50 2 years 1 month Forecasts of sales per families To look for suppliers To negotiate markets To define proc. strategy To define critical proc. To make Long Term plan To define engagement strategy To define structural S/C 40 8 months 1 month Consolidated orders Orders book To define proc. parameters MRP MSP To define conjectural S/C 30 6 month 1 week To send orders to suppliers To make proc. plan To plan workload + MT schedule To define conjectural S/C Inventories level 20 3 months 1 day To recall suppliers To plan workload + ST schedule To assign the personnel Date 10 1 day RT Urgent orders To record orders Title To dispatch To record I/O raw materials, materials and FP 76 PL/30 Example Workload for MT MRP Urgent order 1 To centre the plan over 3 months Workload over 3 months 2 to complete workload Workload over 3 months completed # TO PLAN To plan workload + ST schedule H = 3 months P = 1 day PL/20 # TO PLAN To plan workload + ST schedule MR/10 H = 3 months P = 1 day PL/20 Methodological information PL/30 Progress report on the production PL/30 Objective: Respect of delivery dates DV Delivered quantity Int resour. Man. order PL/30 unreachable 3 Rules Priorities To adjust load (smoothing) Requirement origin MT Workload Load distributed per period and station PL/10 PL/30 Methodological information Date Title 31 32

33 Example: links with the corresponding grid PL/30 MT Workload MRP Urgent order 1 To centre the plan over 3 months Workload over 3 months 2 to complete workload Workload over 3 months completed PL/40 MRP To plan workload + MT schedule PL/30 MR/10 Inventories level PL/30 Progress report on the production PL/30 Objective: Respect of delivery dates DV Delivered quantity Int resour. 3 To adjust load (smoothing) Rules Priorities Requirement origin MT Workload PL/30 To recall suppliers GP/20 PL/10 To plan workload + ST schedule To dispatch PL/20 To assign the personnel GR/20 PL/30 Man. order unreachable Load distributed per period and station PL/10 33

34 Example: links with the corresponding grid Consistence GR/10 Progress report of the production Absent of the grid: normal (additional detail at the level of the nets) To recall suppliers GP/20 To plan workload + ST schedule PL/20 To assign the personnel GR/20 Absent relations in the net: abnormal 34

35 Example: links with the corresponding grid Analysis of the content of the decision framework PL/30 PL/20 In the grid: To plan workload + MT schedule PL/30 PL/30 PL/30 Objective Respect of the delivery date DV delivered quantity Int resour. Transmission of the value of the objective Transmission of the value of the constraints To plan workload + ST schedule PL/20 PL/30 MT Workload Order transmission PL/30 Man. order unreachable Information follow up 35

36 Third THE STRUCTURED part APPROACH 36

37 General principles OBJECTIVES Models Analysis Design Real world Modelling? Existing system (As-is) Implementation Target system (To-be) 37

38 The actors BOARD GROUP Define the objectives and the domain of the study Evaluate and validate the results GRAI Specialists (sensors) Support the study Validation Information Analysis & validation Proposals Validation Information Definition Interviewees Provide information Synthesis group (Main deciders) Perform the study Analysis & validation Working groups Look for solutions Proposals 38

39 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 / 39

40 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 40

41 General progress Initialisation Modelling and existing analysis Context and objectives of of the future system Design of of the future system Actions plan 41

42 Course of the phase «initialisation» Presentation of of the study phases Synthesis group Board Group Groups definition 42

43 Course of the phase «modelling and existing analysis» Global modelling Grid Interviews planning Synthesis group Detailed modelling Interviews Setting form (realisation of the nets) Review of the grid Interviewees Synthesis group Analysis assessment Determination of the inconsistencies Analysis report Synthesis group Board group 43

44 Course of the phase «context and future system objectives» Definition of of the external constraints Synthesis group Definition of of the internal constraints Synthesis group Description of of objectives of of the future system Synthesis group Board group 44

45 Course of the phase «future system design» Design initialisation Global design Inconsistencies solving Proposals for orientations Choice of one orientation Grid Global nets Synthesis group Board group Synthesis group Working groups Detailed design Detailed nets Working groups Design synthesis Design report Synthesis group Board group 45

46 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. 46

47 Example of planning Board Group Synthesis Group Interviews Working Groups The actors Modelling / Diagnosis 3/4 months maximum 3/4 months maximum Double arrow = Framework Design 47

48 Fourth THE INCONSIS- part TENCIES RULES 48

49 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. 49

50 «A» rule Non-sliding horizon Horizons must be sliding. 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 Sliding horizon 0 P 2P 3P 4P = H Revision H+P 0 P 2P 3P 4P = H H+P New forecast 50

51 «A» rule Vision of the future Non-sliding horizon Sliding horizon 4P = H 3P = H-P 2P P 0 P 2P 3P 4P = H 0 H+P 0 P 2P 3P 4P = H H+P 51

52 «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. 52

53 T = L-d «B» rule The horizon must be longer than the time to achieve physical activities of production controlled by the decision centres of the level. Decision centre Controlled activity Duration = d T = L L = delivery date The planning realized at L-d must take the result expected at L into account, then a vision in the future over d is necessary: H d Note : This is true when there is a commitment about the delivery date (generally the case in production management). 53

54 «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 54

55 «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 55

56 «C» rule The value of the period is linked to the frequency of fluctuations impacting the decision centre considered. Shorter the period is, more the system is reactive, Longer the period is, more the system is stable and light to manage. Stability: by implementing «enough» a plan before revising it. Management lightness: less effort with a batch-process of events. Reactiveness Stability and Management lightness Value of the frequency 56

57 «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. 57

58 «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: Order Decision framework 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 P n+1 (period of the upper level). This stability is taken into account by having: H n P n+1 Empirical rule : H n = 2.P n+1 58

59 «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. 59

60 «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. 60

61 «G» rule Configuration that does not match the rule: Decision framework Decision centre Decision framework Configuration theoretically possible (mainly if it exists a unique decision centre upstream the decision frameworks) but not practically recommended. 61

62 «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 Product management Activity management P x R x T Resource management P x T P Product P x R Activity Product R x T Resource R «Activities management»? «Planning» Date Title 26 62

63 «H» rule Example of forbidden configuration: To manage products To plan The decision centre emitter does not master the notion of Resource: it cannot completely frame a decision centre belonging to the Plan function 63

64 «H» rule Possible configurations (for the three elementary control functions): To manage products To plan To manage resources Theoretically possible configuration but forbidden by the G rule: To manage products To plan To manage resources 64

65 «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. 65

66 «J» rule Each elementary control function must have a decision centre at each hierarchical level. P x T Date P Reminder: Activity control Production activity control: basic concepts Product management Product Activity management P x R Activity Resource R Title Resource management Product P x R x T R x T «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. 66

67 «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. 67

68 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.). 68

69 Fifth part THE GRAI METHODOLOGY 69

70 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. 70

71 Modelling domain (by sub-systems) Entity/Relationship or class diagram entity relation entity cardinality entity DECISIONAL SYSTEM H/P GRAI Grid functions INFORMATION SYSTEM trigger PHYSICAL SYSTEM support activity support result control activity support control activity support GRAI nets Actigrams 71

72 Modelling domain: global representation Actigram control FUNCTIONAL VIEW activity support control activity support control extended activity resources logical operator process extended Activity INFORMATION SYSTEM PHYSICAL SYSTEM DECISIONAL SYSTEM PROCESS VIEW resources Extended Actigram 72

73 The offer of specific approaches INDUSTRIAL SYSTEMS ENGINEERING CHOICE AND IMPLEMENTATION OF IT/TECHNICAL/ORGANISATIONAL SOLUTIONS PROGRAI Enterprise process improvement BENCHGRAI Benchmarking GRAI Engineering Product design control GIM Audit GIMSOFT Choice of IT solutions GIM Enterprise modelling GIMPLANT Implementation of solutions ECOGRAI Performance indicators GEM Evolution management enterprise GRAI Message Manufacturing Strategic Plan GRAI Quality GRAI Knowledge PERFORMANCE MANAGEMENT INDUSTRIAL STRATEGY KNOWLEDGE MANAGEMENT GRAI Model Languages Generic approach 73

74 Specific approaches and life cycle Definition of objectives and strategic planning Evolution control oriented SIS oriented Modelling of the existing Diagnostic Target system design Choice/development of technical solutions GIM AUDIT GIM GIM SOFT GRAI ENGINEERING BENCHGRAI GRAI MESSAGE GEM GRAI QUALITY GRAI KNOWLEDGE Implementation of technical solutions GIM PLANT Exploitation/follow up of implemented system ECO GRAI 74

75 Thank you for your attention 75