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© IFAC Distributed Intelligence Systems. Virginia. USA. 1991
A FRAMEWORK FOR DISTRIBUTED INTELLIGENCE TOTAL QUALITY MANAGEMENT SYSTEMS IN THE CIM ENVIRONMENT Baosheng Hu· and A. H. Levis" *Systems Engineering Institute . CIMS Research Center. Xi'an JiaolOng University . Xi'an, PRC 710049 **Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA 22030-4444, USA
ABSTRACT In this paper. an approachto the development of di stributed intelligent total quality management
system~
(DITQMS) for a computer Integrated manufacturIng (CI'v1) environment is pre sented. A comparison study 01 poSSible archItectures of DITQMS In the CIM environment has been made from the viewpoints of technical anc economic realIty for different kind of manufacturing industrie s. To represent the architecture of the DITQMS the IDEFO method has been used and a Colored Petri !\et representation for the IDEFO model is suggested fOl carrying out performance evaluation. Keywords: Total quality management sy stem: total quality control: distributed intelligence: computer integrated manufacturing.
INTRODUCTION
alphanumeric formats also complicates such data base mana~ement system design . And a TQMS may have a number of distributed local decision support subsystems (or mechantsms) to assist quality control decision making at the local level. Thus. the presence of a number of in:elligent nodes exercIsing qualIty management as part of a total quality management system leads to the characterization of such a system as a Distributed Intelligence, Total Quality Management System (DITQMS).
In recent ~ears . progress in computer technology has given rise to Significant Improvement in such domains as master production schedule planning. CAD/CAM, material requirement planning , capacity planning, and on-line control of manufacturing processes. Engineers and scientists are making great effons to integrate these areas, from the current so-called "Islands of Automation" into a total Computer Integrated Manufacturin~ (CIM) environment. Obviously. a CIM system IS a strongly dlstnbuted system. since a manufacturing enterprise consists of vanous depanments or divisions. each of them containing combinations of people. computers. and machines which are dispersed within an enterprise as well as outside the enterprise.
In general, the goal of a DITQMS . implemented with computers connected by networks. can simply described as: (I) Collection of all quality data from all activities in the enter-
prise:
CIM aims at total enterprise automation: its ultimate goal is the full InterconneCllon of all the enterprise functions - from marketinl; and selling to manufacturing and services. including computenzed product design . manufacturing process design . and admInlstrallon - In order to provide productivity and quality Improvement and q~lick adaptation to market changes. But until recently. relatively less attention has been paid to the integration and computer automation of the total quality management (TQM) actiVIties . due to the problem 's complexity in that it covers all activities during the whole product life cycle in the enterprise.
(2) Improvement of production, management. and administra-
Timeliness and quality are the essence of modem production. Often. enllre markets are won or lost on these issue s only. Therefore. the development of a computer-aided total quality management system for CIM has become a crucial element for an enterprise to gain a strong competitive edge in world markets.
Since the quality assurance function under a CIM environment covers all activities during the whole product life cycle, it follows that the TQ'v1S must consider all the quality interactions necessary between the various elements of an enterprise. A conceptual model of a TQMS (Fig. I ) shows the integration of the vanous subsystems m the enterpnse with respect to quality obJectives.
tIon processes by using the collected quality data; (3) Dlstnbutlon of that data to benefit all components of the en-
terpnse; (4) Making quality activity decisions individually in each pro-
cess and synerglstlcally across the processes to attain the product quality desired by customers. or to make the manufacturers low-cost producers of high-quality products. POSSmLE ARCHITECTCRES OF DITQ'v1S
In this paper. an approach to and the problems facing the development of a distributed . intelligent. total quality management system for a CL\1 environment are studied.
The quality objectives can be summarized as maintaining a high level of: Product quality Operator productivity Facility maintenance Customer satisfaction Equipment utilization Quality of raw materials Quality of customer service.
GE!'.'ERAL FEATURE OF THE DITQ'v1S Traditionally. the management system of a modem enterprise is hlerarchlcall~' structured. The attributes of qualit y data in the tIme dimensIOn are timeliness and long life-cycle span: in the spatial . dimenSIOn . they are its dispersi veness across the enterpnse and all related suppliers. Collection of the required qualIty data Involves all aspects of the enterprise. Therefore, the TQ'v1S becomes a hierarchical and highly distributed system. It has many distributed local data bases in quality management depanments for current quality control and management usage. and a centralized data base for total quality decision making , long-term storage. and retrieval of the quality data. The fact that quality data usually are described in graphic . text . and
Also .. the TQ\1 should ~o\'er the systems integration of all the functIons In a product hte cycle including the following stages: Planning Design ~ Procurement
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Production Disoibution Field service.
Which one of these typical TQMS architectures is appropriate for a panicular CIMS depends upon the management philosophy adopted and the quality control requirements expected in (or desired by) a panicular manufacturing industry. For example, if the Just-in-Time (JIT) management and Kaizen quality control philosophy are adopted, then a completely embedded architecture of TQMS will result. Similarly, for a relatively small scale CIMS , it is preferable to use the completely embedded architecture for its TQMS. For these two cases, the computer resources for the management information system (MIS) of the enterprise are also used for TQM purposes. But for a large scale manufacturing enterprise, such as an aircraft company, it is advantageous to use the panially independent architecture with hierarchical and distributed structure for its TQMS.
Each of these functions needs to be integrated with respect to qUality objectives. It is only then that the quality of output at each stage of the total process will be preserved throughout the subsequent stages.
Analysis of the two architectures shows that because of technical considerations and economic reality, the completely embedded architecture of DITQMS is more appropriate for small scale CIM enterprises, while the panially independent architecture is appropriate for large scale manufacturing enterprises. DESIGN OF DITQMS In order for the DITQMS to be compatible with CIM, the principles suggested by Hughes and Maull (1985) listed below are adopted: top-down approach modularity minimization of coupling prototyping user involvement planned evolution
Fi9. 1 Conceptual Model of TQMS In principle, individual quality control systems should be designed according to these functions and then integrated. to form a total quality control management system. The mtegratlon of quality systems can be viewed as the management of quality information in terms of a combination of sensmg, communication, processing and evaluation elements in such a way as to achieve the quality objectives and facilitate the overall manufacturing and financial goals of the enterprise . Thus, quality system integration can be considered in three dimensions:
With these principles in mind, a methodology developed for the design and evaluation of organizations supponed by information and decision systems (Levis, 1988) is being adapted to the DITQMS problem. This methodology is based on the ability to express in commensurate terms the physical architecture and the functional architecture of a system and relate the physical entities to the specific functions to be performed. One technique that is being increasingly used to represent the functional architecture of a manufacturing system is the Structured Analysis and Design Technique (SADT) (Marca and McGowan, 1988) and its software implementation, IDEFQ.
venical integration - among the quality systems functional integration - with other CIM subsystems process integration - through the production stages.
An IDEFO diagram (or set of hierarchically structured diagrams) contains two graphical elements, boxes and arrows. The rectangular boxes represent activities (or functions) of the system being modeled; the arrows represent interconnections between boxes. The anows can represent four different kinds of relationships between functions: (a) inputs; (b) outputs; (c) controls; and (d) mechanisms. The formal representation of these relationships is shown in Figure 3. This is called the ICOM (Input, Control, Output, Mechanism) box to remind one of the four types of relationships that can be represented.
Depending on the way the integration along the three dimensions is carried out, different architectures of TQMS are obtamed. But the hierarchical and distributed nature of the underlying system is still maintained in the different possible architectures. Three typical architectures as shown in Fig. 2. They are : (a) the completely embedded, (b) the totally independent, and (c) the partially independen/ architectures.
TQMS
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Figure 3. The ICOM or Activity box in IDEFQ. Implicit in the representation of the function box is an activation rule of the form: When the preconditions are met , i.e., there is an input, there is a mechanism or resource available, and the control enables the activity, then the activity is performed and the output is generated. Consider, for example, the one-box representation of the manufacturing of a pan (Figure 4). This is
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Fig. 2 Possible Arcbitectures of TQMS
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usually referred to as the AO or source diagram for this process. The input to the manufacturing process is the material from which the pan is to be manufactured. The control is the set of product manufacturing requirements as expressed, for instance, by a set of blueprints. The mechanism represents the set of tools needed to conven the material into the pan specified by the control. Two outputs of the process are shown: the pan and data about the manufacturing process. The latter is the output used in the TQM process. To complete this diagram one needs to add explicitly the purpose of the model being built (e.g .. to represent the TQM system for a panicular manufacturing process) and the viewpoint. In this case it could be the viev. point of the TQM system designer.
correspondence between IDEFo boxes and Petri Net transitions is clear. Difficulties arise in determining the equivalence of arrows. In IDEFo. the arrows can carry many things and can branch and join. In converting these arrows to Petri Net connectors, it is necessary to state explicitly what each arrow carries and. when an arrow branches, to state clearly what information is carried by each branch. The key is that to obtain an executable model, it is necessary to add information to the IDEFo model to resolve ambiguities. Fonunately, commercial software has become recently available that has automated to a substantial extent the conversion of IDEFo diagrams to Colared Petri I\"et models . (Two products of Meta Software Corp. of Cambridge. MA. namely. designllDEF "'and designICPNT" , work together to accomplish that. One constructs an IDEFO diagram using design/lDEF and . when the diagram is complete and has been checked and reviewed. one executes a sequence of commands that help convert the IDEFo diagram into a Colared Petri Net (CP:--.'). Note that CPNs have syntax requirements that constrain the structure of an IDEFo diagram that is to be convened to a CPI\" (Meta Software Corp .. 1989). One needs to inscribe places. transitions. and connectors with the appropriate Color sets and initial markings for places: guards for the transitions, and arc expressions for the connectors. The global definition includes the definition of every color set in the net , pointers to every place to which each color set applies , the definitions of each variable in the model. and pointers to the arc expressions where each variable appears. The fact that the IDEFo model appears on a set of pages hierarchically structured implies that the Petri i'iet will also appear in a set of pages structured in the same way. Therefore , in addition to global definitions, one can include local definitions that apply to a page. The page structure can be used to delineate the intelligent nodes in the DlTQM system: the interconnections between pages specify in a direct way the locations where communication channels must be established to transmit information from one node to another and from a lower level to a higher level of the hierarchy.
Product Manufacturing Requirements
Materials
Manufacture Pan Pan 1 - - - -..... '--_-..__..\_0-, \1anufacturing In formation
Production Resources Figure 4. The source diagram for a manufacturing process. The next step in the construction of the TQM model is to decompose the AO diagram hierarchically using the syntax rules of SADT (or IDEFo). The decomposition is carried out until the individual functions (boxes) represent indivisible processes from the chosen viewpoint. It is at this lowest level that the establishment of the correspondence between functions and equipment (tools , computers, communication links, instruments, etc.) is most direct and unambiguous.
The CPN derived in this way can then be read by designlCPNTM and executed using the embedded simulator. Carrying out a series of computer simulations allows one to obtain performance measures that characterize the timeliness (Cothier, 1986) of quality data and to assess the dispersiveness of the quality data across the various functional units of the enterprise and all the suppliers to the enterprise.
Once the model of the existing TQM system is obtained, the designer has to consider the distribution of the functions to a number of nodes and the allocation of the appropriate resources to those nodes so that they can be intelligent. The notion of distribution used here is that of Minsky (1987) who has defined as distributed systems in which each function is carried out in part by a different node and where each node execute subfunctions of a number of different functions. The functionality described by the IDEFO model of the TQM system is now distributed and the DlTQM system model model is obtained. This is a non-trivial step in which the designer takes into consideration the organizational structure of the enterprise (one aspect of the physical architecture) and the geographical location of the resources of the enterprise. Once the functions (and subfunctions) have been distributed . the information flows are determined . Each function establishes requirements for input data or information and generates new data that can be transmitted for use by other functions . The determination of what local quality data ba,e needs to be implemented at each node and what information has to reside at the higher levels of the system are imponant design questions at this stage.
This problem is analogous to the development of a consistent and coherent tactical picture across the key platforms that constitute a naval battle force. Sensors distributed across the ships, aircraft. and other resources of the battle force collect data at various times and with different degrees of accuracy and generality. These data are processed locally and information is transmitted over diverse communications nets among the platforms of the battle force. Different commanders, depending on their warfare mission area such as anti-air or antl-submanne, need different information in different degrees of accuracy and detail. But all the tactical pictures must be consistent, so that all the commanders observe aspects of the same " world, " and coherent so that they all percei ve the same general situation Bonwit et a!.. 1990) Once the simulations are executed and the results indicate that the DlTQM is executable . i.e .. it works without logical errors. performance evaluation is carried out. This is done in two steps. In the first step. the Petri ;'Iiet representing the TQM system IS analyzed to determine the embedded functionality using a technique developed by Valraud and LevIS (1989). At thIS time, the technique can be applied only to ordinary Petri :--.'ets because it is based on the ability to determine algorithmically the place invariants (s-invariants) of a net. Therefore. It becomes necessary to extract a number of ordinary Petri Nets from the CPN and apply the algorithm to each net. The techmque leads to the determination of all the flow paths from sources of data (sensors) to outputs (quality measures) as well as the subnets that indicate all the information flow paths that contnbute to a a panicular quality measure . The same procedure is applied to the DITQM system net and a comparable , but larger. set of subnets is obtained. The two sets are compared to determine whether any functionality present in the TQM system has been lost In the design of the DlTQ\1 system (shonfalls).
There is no analytical procedure that allows the distribution of the functions to be carried out in an optimal way in an already existing enterprise: the distribution of the physical resources and the organizational Structure constitute dominant constraints. As a result . it becomes panicularly imponant to have the ability to carry out performance analysis of the proposed DlTQM system. However. the IDEFo model. while quite useful and intuitively appealing especially for elicitation of information about the various stages of the process from enterprise personnel, is not an executable model. To accomplish the latter. the Colored Petri Net formalism is introduced. Colared Petri :'\ets are one type of Higher Level Petri :'\ets in which the tokens are distinguishable. i.e .. they carry with them a set of attributes (the color) which can be changed as processes take place. There are some useful correspondences between IDEFo diagrams and Petri :'\ets. but the correspondence is not complete. Petri :'\ets are bipanite directed graphs. i.e. , they have two types of nodes (transitions and places) while the arrows or connectors indicate an ordered relarionship between nodes. The
In the second step. attribute values are introduced such as delays associated with each transition . and measures of timeliness are obtained. For example. delays in transmitting quality data from a 10wer level in the hierarchy to a higher one and the effect that delay has on Total Quality Management can be studied.
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When the designer is sarisfied rhar rhe proposed DITQ:vI design is satisfactory. i.e .. ir meets the requirements. then he has to design the straregy thar will result in a trajectory that will move the exisring TQM sysrem from its current state to rhe DITQM system design .
CONCLUSION A framework for rhe design and evaluation of Distribured Inrelligence Toral Qualiry management sysrems appropriare for use in conjunction with CompUler Integrared :vIanufacturing has been presented. The quantirative aspects of the approach are based to some extent on methodologies. rechniques. and tools developed in recent years for the design and evaluarion of command and control archirecrures and of the sysrems. rhe C3 systems. that support rhem. A first applicarion of these techniques is proceeding in several DITQ:vI design projecrs in China. The objective is to improve proposed architecrures so that all aspecrs of quality management can be coordinated across a whole enterprise and its suppliers.
The final srep consisrs of the detailed plan for the implementation of the new design . This includes the purchase and allocation of hardware. software. and data bases. Therefore. the proposed design process described above consists of seven stages: Construction of an IDEFO model of the exisring TQ:vI system. Consrrucrion of an IDEFo model of the proposed DITQM sysrem. Transformarion of rhe IDEFo models of rhe exisring TQM sysrem and rhe proposed DITQ:vI sysrem into Colored Perri "er models. Strucrural analysis. compurer simularion and performance evaluarion of rhe rwo Colored Perri :-.Iers. Revision of rhe proposed DITQM sysrem to improve, as needed. rhe coordinarion of TQ:vI acriviries across rhe enterprise and irs suppliers. Comparison of rhe models of rhe exisring and revised systems ro identify the planning space and rhe seiewon of an appropriare straregy to move from the existing to the revised DITQM sysrem. Detailed design and implementarion of DITQM sysrem including hardware allocation . software. and data bases.
REFERE;\CES Badiru. A.B. (1990). A systems approach to toral qualiry management. Industrial Eng. 3. 33-36. Bonwit. W. R.. T, Kidd. and A. H. Levis (1990). Banle Force Level C31 Assessment Methodology. Proc. 1990 Symposium on C2 Research. SAle. '\1cLean. VA. Cothier. P.H. and A. H. Levis. (1986) Timeliness and measures of effectiveness in command and COntrol. IEEE TraIlS. on SMC. SMC-16. "0.6. Crossfield. R.T. (1990) Mapping quality assurance systemsJ a methodology. Quality & Reliability Eng, Imemat. 6. 167-178. Harhalakis. G.. C.P. Lin and L. Mark. (1989). A knowledgebased prototype of a factory level CIM system. Computer. Integrated Manufa cturing Systems. I. 11-20.
DATA BASES In rhe DITQM sysrem. the qualiry darabase assumes grear imponance as an integraring mechanism and acrs as rhe hub of rhe sysrem. The darabase sysrem for DJTQMS has borh hierarchical and disrribured fealUres. The rarionale for a distribured database srrucrure is rhe minimization of data transfer and dara access/ITansfer rime by storing qualiry informarion close to the local user. i.e .. at rhe intelligent nodes of rhe sysrem model. The hierarchical principle ensures rhar qualiry information of a more general narure is stored at rhe higher levels in rhe sysrem and rha! of a more detailed nalUre at rhe lower levels. This is in line wirh the manner in which quality decisions are made on the basis of different rypes of quality information within rhe CIMS. Therefore , the design of such database system and its management system (DBMS) becomes a critical aspect of the overall design.
Harvey. G. (1990) The strategic development of manufacruring through total quality. Proc. of Manufa ctllring Systems Toward the Twenry· First Cenrury. (Kyoto. Japan ) 35-38. Hughes. D. and R. S. :vIaull (1985) The design architecture for CIM systems. Proc. Con! Computers in Engineering. Boston. USA. Levis. A. H. (1988) Human organizations as distributed intelligence systems. Pro c. IFAC Symposium on Distributed Inrelligence Systems. Pergamon Press. Oxford . England. Marca. D. A.. and e. L. McGowan (1988) SADT: Structured Analysis and Design Te chnique. McGraw-Hill. New York. Meta Software Corp. (19890 desigIl.'IDEF'" User's Manual , Meta Software Corp .. Cambridge. MA.
In addition to the quality information flow structure depicted in the IDEFo diagram and used in the simulation. there is also the quality decision structure as represented by the control arrows formalism. This decision structure shows the way in which quality information is used to affect the producr quality, both at the local level and at the total. enterprise level.
Minsky. :vi. (1987) Th e Sociery of .'vtind. Simon and Schusrer. New York. Pun. L. (1988) \1ethodology for structuring distributed intelligence in computer-aided production management. Proc. IFAC Symposium on Distributed Intelli ge nce SYStems. Pergamon Press. Oxford. England. 55-67.
CCRRE!"T DITQ\1S PROJECTS IN CHl,\A In order to benefit from Computer Integrated :vIanufaCluring and the progress made in CS. Japan and Wesrern European countries. a Cl MS Re search Project has been Ulcluded 111 the Hitech Plan in China. which was initiared in 1986, The CI:vIS Research Project includes the establishment of a te st bed for CIMS and seven research centers. The research center that is dedicated to the development of total quality !Tlana~ement techniques for the CI\1 em'ironment is located III XI an l1aorong University. Since 1989. four large manufactunng enterpnses have been selected for applying CI:vI techniques and the seven research centers have assumed the responsibility for help1l1g rhem to dnelop CI\1 teChniques that are appropriate to each type of enterprise.
Smith. G.W. and \1ing Wang . (1989) \-lodelling CIM sysrems Part Ill: an intelligent database design environment for the design and implementation of a Cl:vl information system. Computer·lmegrated Manufacturing Sysrems. 2. 99·107. Tannock. 1. D. T. and R. S. \1aull. (1988) The integrated quality system in CI\1. Computer·lmegratcd .\1anujacturing Systems. -+. 228·23-+. Valraud. F. and A. H. Levis (I989) On the Quantirative Evaluation of Functionality in Distributed Intelligence Systems. Proc. 1989 IEEE InO Srmp. on Imelligenr Comrol, Albany. "Y.
The TQM Research Center in Xi'an Jiaotong Cniversity has been assisting three enterprises to dew lop TQ\1 sysrems for CIM : an aircrafr manufacturing company. a tex!lle mach1l1ery company. and a machine tool factory. \Iost recently. the preliminary design of DITQ:vIS for one of these three enterpnses was complered. and rhe detaJled deSIgn and development are under way. The preliminary design of DITQ\1 sysrems for the other two enterprises will be completed by August 1991 ..These three DITQ:vIS projects are expecred to be completed wIth m five years. Description of the actual designs and results achIeved will be presented in future papers and repons.
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