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MES and CIM (Computer-Integrated Manufacturing)

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CIM and its Relationship to Manufacturing Execution Systems (MES)

CIM (Computer Integrated Manufacturing) is an overall framework for using computers to manage plants and business. This terminology was popularized for the process industries by the Computer Integrated Process Operations Consortium (CIPAC), a former academic/industrial consortium sponsored by Purdue University. (Greg Stanley was an industry representative to CIPAC for many years).  In recent terminology, integration software and some levels of CIM would be considered MES (Manufacturing Execution Systems).  However, CIM is a broader concept, covering all levels in the plant and enterprise computing framework (rather than just emphasizing functionality in between process control and enterprise resource planning in the plant computing hierarchy).  It also can address common knowledge stored in currently-disparate systems as well as the interfaces between those systems.

A knowledge-based approach to CIM

Traditional approaches to CIM involve numerous data interfaces between applications. Some emphasize a centralized data base or a hierarchical structure. However, traditional approaches suffer by focusing on data flow: (1) Redundant, possibly inconsistent model information is encoded in multiple applications, complicating development and maintenance, (2) Plant models are not explicit enough for easy review by many people, and (3) Multiple developer and end-user interfaces exist. In reality, there is more commonality between applications than just the data. For instance, multiple applications such as scheduling, control, optimization, simulation, monitoring, and diagnostics all need common information, such as: connectivity from plant schematics, recipes, manufacturing procedure sequences and constraints, routing information, equipment information, part-of relationships, and goals. Much information about products, equipment, events, and paperwork can be best organized into classification hierarchies, formalizing commonalities.  A knowledge-based approach to capturing and re-using plant knowledge for multiple applications is required. Knowledge-based systems reduce the gaps between analysis, specification, design, and implementation. Much of the knowledge is in a declarative form, accessible and inspectable by both developers and end-users. Qualitative model-based reasoning (e.g., expert systems), and quantitative algorithms such as LP and other optimization techniques, require common model information.

The following white paper, presented at the 1994 ISA conference, compares various overall CIM reference models and architectures to support plant-wide computing.  Successful examples of computer-integrated operations using newer knowledge-based, network implementations are given.

The Emerging Trend Towards Knowledge-Based Frameworks for Computer-Integrated Manufacturing (pdf)

An earlier paper on this topic is

V. Venkatasubramanian and G. M. Stanley, "Integration of Process Monitoring, Diagnosis and Control: Issues and Emerging Trends", in the Proceedings of the International Conference on Foundations of Computer Aided Process Operations (FOCAPO'93), Crested Butte, CO, July 1993.


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