Knowledge based product life cycle systems: principles of integration of KBE and C3P

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Abstract

Future computer-aided design systems will provide a suite of tools capable of managing the entire product life cycle. Knowledge Based Engineering (KBE) systems will be used to support many aspects of the product life cycle. For a variety of reasons, we believe that CAD developers should not attempt to provide the required KBE functionality as part of their product. Rather, the CAD systems should be built with a fully open architecture to allow easy integration of a broad range of KBE software.

Introduction

The continuing evolution of product design tools from the drafting board to the computer screen will soon leave the present description CAD systems behind. Companies purchasing future high-end design systems will expect a suite of tools capable of managing their entire product life cycle. These new systems will present many new opportunities for integration of existing and future Knowledge Based Engineering (KBE) systems to support various aspects of the product life cycle. KBE tools that were stand-alone systems in the past will need to be tightly integrated with these new comprehensive design environments, in order to achieve maximum benefit.

The purpose of this paper is to discuss certain aspects of the software architecture of future product design systems that will be critical to the successful integration of KBE functionality. We begin by describing what we believe future CAD system will be like, and the general characteristic of KBE systems that will need to be integrated with them. Then we will detail the software design requirements necessary to successfully bring these two technologies together. Although we discuss several examples of KBE systems, it is not our intention to detail the implementation of KBE systems themselves. The various techniques for knowledge representation and processing—for geometry-oriented and other knowledge based systems—are well known; we do not explore them here. Recognizing that there is not one best solution for the knowledge representation problem, we believe the CAD system requirements discussed here will enable multiple solutions, each specific to its various domain, to be integrated deeply and effectively into the CAD environment.

Section snippets

Product life cycle systems

Increasing competitive pressures and higher customer expectations are compelling every manufacturing company to seek out greater efficiencies in each step of their product life cycle: planning, design, engineering, manufacturing, distribution and support. With their large and complex product lines, automotive manufacturers are particularly affected by these demands. As new computer systems are designed to support efficiency improvements in all these life cycle areas, it is inevitable that the

Knowledge based engineering

A rigorous definition of KBE has proven elusive, for a very simple reason: no engineer wants to admit that they are not, in some sense, engaged in a ‘knowledge-based’ activity, no matter what their job entails exactly, or how they go about doing it. This is perfectly understandable. Even so, for the purposes of specifying and developing software systems to support KBE, it is useful to define KBE and distinguish those systems as a class. In particular, for the purpose of this paper, we wish to

Integration of KBE and CAD

In considering the integration of KBE functionality into the CAD environment, essentially two options present themselves. One option is for the CAD system developers to provide KBE functionality as an integral part of their CAD environment, either by developing that functionality themselves or by partnering with a KBE software developer and integrating an existing KBE tool. The alternative is to provide an open Application Program Interface (API), thereby allowing the user to interface any kind

Product life cycle system architecture and principles of integration

Fig. 1 shows how the traditional Product Development applications will mesh with KBE enablers within the new PLCS. The next several sections will propose an integration scheme and give individual examples of key capabilities required to enable KBE.

CAD

The ‘CAD the Master’ philosophy has grown with the complexity of the design systems to include more than just part geometry and drawing information. Modern CAD environments contain flexible, robust, variational/parametric tools with feature/part/assembly management database capability. The benefit to the Knowledge Engineer is that the new capabilities of the CAD system allow the user to put more knowledge into the model. The downside to this is that there is now a choice of where to store the

CAE

The inclusion of an integrated analysis tool in the product development suite is a key strategic advantage to the company able to use that tool to improve their product and reduce their time-to-market. Integrated tools allow analysis of the latest design proposals and optimization of part geometry directly. Experienced analysts are valued for their ability to build computer-based models whose behaviors closely resemble physical test results. KBE systems can encapsulate this experience, automate

CAM

The CAM component of the PLCS will benefit from the additional information and knowledge placed into the system upstream. KBE will allow the designers to realize cost and produceability benefits upstream of the CAM system by providing feasibility analysis and component/feature selection in the CAD system. Intelligent catalog selections based on historical quality, or complexity reduction efforts increase quality and reduce cost. Integrated design and manufacturing systems are not only

Product database

The PIM/EDM systems will see dramatic expansion in new systems. Current systems are so varied in approach and capability that, for this discussion, we will assume that the PIM system consists of a customized database management system that manages all models created by the CAD/CAE/CAM system, as well as linked foreign data. The term manage includes revision control and notification of users and owners of parts. Because of the highly customized nature of these systems, they are typically

KBE technologies

Regardless of the usage or architecture model of previous KBE systems, a logical progression would be for the KBE systems to move in the direction of knowledge acquisition. Integration with the above systems and technologies like data mining may be useful for this.

The KBE tool should include the capability to take advantage of a range of algorithmic and Artificial Intelligence technologies to solve problems. These will include Expert Systems, Genetic Algorithms, Neural Networks and Constraint

Conclusion

Future computer based design tools will provide a broad range of functionality to support the entire product life cycle. Integration of knowledge based engineering capabilities and other enabling technologies will be achieved through open systems design. As the software continues to evolve, open architectures will provide the best solution for quickly capitalizing on new developments in CAD, CAM, CAE, PIM, and KBE.

Acknowledgements

The authors would like to thank their co-workers who aided them in the preparation of this paper: Jack Hengehold of Structural Dynamics Research Corporation; Y. Stephen Sheng, Yong Pan, Tim Premack and Chi Wang of Visteon Corporation and Nanxin Wang of Ford Motor Company.

John A. Penoyer, Jr. is supervisor of KBE Planning and Deployment at Visteon Automotive Systems, an enterprise of Ford Motor Company. Mr Penoyer earned a BS in Mechanical Engineering from the Clemson University in 1989, and has been a KBE practitioner for the past 10 years, beginning with tooling projects for The Boeing Company using ICAD and CATIA. As a consultant for Stone and Webster ASDS, he developed KBE application for automotive, aerospace and manufacturing companies using Pro/E and

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John A. Penoyer, Jr. is supervisor of KBE Planning and Deployment at Visteon Automotive Systems, an enterprise of Ford Motor Company. Mr Penoyer earned a BS in Mechanical Engineering from the Clemson University in 1989, and has been a KBE practitioner for the past 10 years, beginning with tooling projects for The Boeing Company using ICAD and CATIA. As a consultant for Stone and Webster ASDS, he developed KBE application for automotive, aerospace and manufacturing companies using Pro/E and CATIA. Mr Penoyer joined Ford Motor Company in 1995. While at Ford, he has prototyped KBE systems within the I-DEAS C3P environment, and developed the CAE process for the Ford Product Development System (FPDS).

Greg Burnett is a Supervisor of KBE Systems Development at the Ford Motor Company. Mr Burnett holds BA and MS degrees in Computer Science from Southern Illinois University. He joined Ford in 1976, and has specialized in Artificial Intelligence and Expert Systems since 1985. Mr Burnett has built intelligent systems for a variety of applications in finance, manufacturing and engineering. He is presently supervising the development of intelligent software tools for product design and engineering in an integrated CAD/CAM/CAE environment.

David J. Fawcett is Manager of KBE Systems Development at Ford Motor Company. Mr Fawcett joined Ford in 1968 as part of the Computer Graphics project. He was on the PDGS development team until 1976, when he joined the Electronics Division. There he developed CAD tools for printed circuit boards and mathematical modeling. Mr Fawcett began developing AI applications for CAD/CAM at electronics division in 1986. He was Operations Research Manager under Ford 2000, and is now KBE System manager in Product Development Systems in FAO. Mr Fawcett has been involved in developing many CAD, CAE and KBE applications at Ford over his career. He holds Bachelors and Master Degrees in Electrical Engineering and a Masters Degree in Artificial Intelligence.

Dr Shuh-Yuan Liou is Manager of the Knowledge Based Engineering Department at Visteon Automotive Systems, an enterprise of Ford Motor Company. Dr Liou received his PhD in Industrial and Systems Engineering from Ohio State University in 1990. He has taught graduate courses in Concurrent and Knowledge Based Engineering at Wayne State University. Dr Liou worked for three years at General Motors as Project Manager developing the DFM Advisor for Body Sheet Metal Design. Since joining Ford in 1993, he has invented Design Advisors for Die Casting and Injection Molding and has developed several KBE systems and applications that are currently in use or in prototype stages. Dr Liou has a number of patents pending for KBE systems and DFM Design Advisors, and has published several papers on related topics.

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