Expert Systems In Manufacturing Research Articles

Plastic additive manufacturing expert systems for small and medium automotives industries

The additive manufacturing basic techniques are ideal for swiftly fabricating items and evaluating their functionality, making them ideal for fast prototyping. Lighting, automotive parts, consumer electronics as well as on-demand items are among the industries where it is most extensively used. Currently, there are various types of additive manufacturing processes and also various research of future processes. Each of the processes will give different results for the user’s product as various parameters are involved. Therefore, the process selections can become problematic and challenging since additive manufacturing requires specification and knowledge in order to create a product with the most suitable additive manufacturing process. This research will serve the purpose of providing knowledge of the additive manufacturing process through an expert system. Expert systems have been widely used in providing solutions and to obtain the knowledge of certain information. This study will take on the challenge of gaining sufficient knowledge in additive manufacturing pertaining to its selections which will be presented through the set of an expert system in the software MATLAB that is being used. The methods of obtaining the information and providing solutions will be the key structure for this research. Therefore, the expected result for this research is to provide knowledge information on additive manufacturing process and also for its process selections that will be set up from the expert systems applications.

The Role of Expert System in Manufacturing Spare Parts for Developing Nations.(Dept.M)

Many of the developing nations facing difficulties in providing the required spare parts needed to their industries, which in turn make them suffer economical and technological buckwardness. This paper defines the spare part problem, then describes the basic conceptual methodology of spare part local manufacturing expert system, as well as the necessarily concepts needed to make such expert system worth it in the developing nations.

A novel approach to DFM in toolmaking: a case study

A novel approach to avoid the knowledge gap between design and production is presented in this paper. The main idea is to build a system in the form of a computer program whose core is the manufacturing expert systems to be used by the product designer. The system reveals critical features of the designed product from the manufacturing point of view and points them out to the product designer. The product designer can decide whether to change the critical part of the product or not. The system presented in this paper is prepared for the toolmaking, where a lot of relatively cheap products are made by one relatively expensive tool. Since the shape of the cavity in the tool is the negative shape of the product, small changes in the product design can significantly reduce the manufacturing costs of the tool.

Empirically Testing Some Important Factors for Expert Systems Quality

Improving expert systems (ES) quality becomes increasingly important as widespread use and company dependency on ES increases. Six major variables (developer skills, user characteristics, expert characteristics, shell quality, user involvement, and management support) were identified and tested in this study. IBM's Corporate Manufacturing Expert Systems Project Center collected information on 69 projects from project managers and end users to enable the study. The results clearly support the hypothesized relationships and suggest the need for ES project managers to pay special attention to these determinants of ES implementation quality. For exploratory purposes, the component items for each of these major variables were correlated with the components of ES quality. Based on the results, several recommendations are proposed for ES project managers to enhance project quality, including: increasing ES developer training to improve their people skills and ability to model, and to use a systems approach in solving business problems; shaping end-user attitudes and expectations regarding ES; improving the selection of domain experts; restricting the acquisition of ES shells based on a proposed set of criteria; and ensuring a proper match of ES development techniques and tools to the business problem at hand.

Ask the expert [manufacturing expert systems

Manufacturers are realising that one of the most cost-effective ways to improve productivity is to invest in information technology. The author explains that the latest knowledge-based systems are truly 'expert' in their application.

A Surface Area Calculation and CAPP System for Non-Axisymmetric Deep Drawing Products

In this paper a surface area calculation for non-axisymmetric deep drawing products of elliptical shape was constructed for the design of blank shapes of deep drawing products by using an AutoLISP function in AutoCAD software. A computer-aided process planning (CAPP) system for rotationally symmetric deep drawing products has been developed. In this study, a CAPP system for non-axisymmetric deep drawing products of elliptical shape was constructed using process sequence design. The system developed consists of four modules. The first is the recognition of shape module for recognising non-axisymmetric products. The second is a 3D modelling module for calculating the surface area for non-axisymmetric products. The third is a blank design module for creating an oval-shaped blank with an identical surface area. The fourth is a process planning module based on production rules that play the most important role in an expert system for manufacturing. The production rules are generated and upgraded by interviewing field engineers. The drawing coefficient, the punch and die radii for elliptical shape products are considered as the main design parameters. The suitability of this system was verified by applying it to a real deep drawing product. This surface area calculation and CAPP system should be very useful for reducing the lead-time for manufacturing and for improving the accuracy of products.

Application of computer-aided process planning system for non-axisymmetric deep drawing products

A computer-aided process planning system for rotationally symmetric deep drawing products has been developed. The application for non-axisymmetric components however has not been reported yet. Thus, this study investigates process sequence design and constructs a computer-aided process planning system for non-axisymmetric deep drawing products with elliptical shape. The system developed consists of three modules. The first one is three-dimensional modeling module to calculate surface area for non-axisymmetric products. The second one is a blank design module that creates an oval-shaped blank with the identical surface area. The third one is a process planning module based on production rules that play the best important roles in an expert system for manufacturing. The production rules are generated and upgraded by interviewing field engineers. Especially, drawing coefficient, punch and die radii for elliptical shape products are considered as main design parameters.

Exploring the factors associated with expert systems success

As the widespread use and company dependency on Expert Systems increase, so does the need to assess their value and to ensure implementation success. This study identified and empirically tested eight major variables proposed in the literature as determinants of ES success, in this case measured in terms of user satisfaction. IBM's Corporate Manufacturing Expert Systems Project Center collected information from 69 project managers to support the study. The results clearly support the hypothesized relationships and suggest the need for ES project managers to pay special attention to these determinants of ES implementation success. ES success is directly related to the quality of developers and of the ES shells used, end-user characteristics and degree of user involvement in ES development, as each has been defined in this study. For exploratory purposes, the component items for each of these major variables were correlated with the components of user satisfaction. Based on the results, several recommendations are proposed for ES project managers to enhance the likelihood of project success, including: adding problem difficulty as a criterion for ES application selection; increasing ES developer training to improve their people skills, ability to model and to use a systems approach in solving business problems; shaping end-user attitudes and expectations regarding ES; improving the selection of domain experts; more thoroughly understanding the ES impact on end-user jobs; restricting the acquisition of ES shells based on a proposed set of criteria; and ensuring a proper match of ES development techniques and tools to the business problem at hand.

Knowledge‐base construction of a garment manufacturing expert system

Focuses on Korean garment manufacturing and the feasibility and benefits of introducing an expert system. Reviews previous literature on knowledge‐based system and describes in detail the stages followed in developing, constructing, testing, evaluating, integrating, implementing and maintaining the expert system. Concludes that an expert system could be used to solve various garment manufacturing problems and would contribute to garment quality improvement through a standardized apparel production process.

Success factors for manufacturing expert system development

As a testimony to their success, the use of Expert Systems (ES) has increased dramatically within and among manufacturing organizations. As the investment in this important area grows, so does the need for an assessment of their value. IBM's Corporate Manufacturing Expert Systems Project Center collected information from 55 project managers regarding the level of user satisfaction and six of the important factors leading to ES development success. Based on the existing literature, six hypotheses regarding the determinants of ES development success as measured by user satisfaction were tested. The results clearly support the proposed relationships between the variables and suggest the need for ES project managers to pay special attention to these determinants of user satisfaction with ES. The report provides recommendations to ES project managers for enhancing the likelihood of project success.

Assessing Expert Systems Impact on Users’ Jobs

A comprehensive list of ten major expert systems (ES) related factors likely to affect users' jobs has been defined, including problem importance, problem difficulty, developer skill, domain expert quality, user characteristics, user satisfaction, shell quality, user involvement, management support, and system usage. Impact on the job has been defined in terms of eleven items dealing with changes in job importance, amount of work, accuracy requirements, skills needed, job appeal, feed-back about performance, freedom in how to do the job, opportunity for advancement, job security, relation with peers, and job satisfaction. Data were collected on sixtynine expert systems developed through IBM's Corporate Manufacturing Expert Systems Project Center in San Jose, California. The results show that the major variables having the most impact on users' jobs are problem importance, problem difficulty, domain expert quality, user satisfaction with the ES, shell quality, and user involvement in ES development. Based on the results, recommendations are made for corporate and ES development managers to increase the likelihood that ES will have a desirable impact on users' jobs.

Exploring the Factors Associated with Expert Systems Success

As the widespread use and company dependency on expert systems (ES) incease, so does the need to assess their value and to ensure implementation success. This study identifies and empirically tests eight major variables proposed in the literature as determinants of ES success, in this case measured in terms of user satisfactions. IBM's Corporate Manufacturing Expert Systems Project Center collected information from 69 project managers to support the study. The results clearly support the hypothesized relationships and suggest the need for ES project managers to pay special attention to these determinants of ES implementation success. ES success is directily related to the quality of developers and the ES shells used, end-user characteristcs, and degree of user involvement in ES development, as each has been defined in this study. For exploratory purposes, the component items for each of these major variables were correlated with the components of user satisfaction. Based on the results, several recommendations are proposed for ES project managers to enhance the likelihood of project success, including: adding problem difficulty as a criteriaon for ES application selection; increasing ES developer training to improve people skills; having the ability to model and use a systems approach in solving business problems; sharping end-user attitudes and expectations regarding ES; improving the selction of domain experts; more thoroughly understanding the ES impact on end-user jobs; restricting the acquistion of ES shells based on a rpopsoed set of criteria; and ensuring a proper match of ES development techniques and tools to the business problem at hand.

Utilization and Benefits of Expert Systems in Manufacturing

An analysis of survey data collected from a sample of 98 Fortune 500 industrial companies reveals that expert systems (ESs) are utilized in manufacturing by 52 per cent of the companies, among which ESs are perceived to be more useful in process planning, product design, layout, facility design and maintenance; and less useful in forecasting production demand and reducing accidents/ safety hazards. Some suggestions are offered on integrating ESs with simulation and logistical knowledge, and involving top management in ES development projects to maximize the pay‐off of utilizing ESs in manufacturing.

The development of a feature-based fixture process planning system for flexible assembly

The use of expert systems in manufacturing is steadily increasing. The majority of these systems are designed to perform process control or to diagnose process malfunction. Though quality control is generally not an explicit development goal, a number of manufactures have realized quality improvements from the use of expert systems. The premise of this paper is that, instead of accepting quality improvements as a windfall from the development of intelligent systems, manufacturers could benefit from expert systems designed to support quality management activities. General object-based architectures for expert systems developed from the principles of two proven quality management methods—Quality Function Deployment and Quality Planning—are proposed.

Expert systems in manufacturing. Part 2: A management framework for expert-systems innovation and technology transfer

Abstract Current approaches to expert systems technology transfer have tended to focus upon the marketing and servicing of technology capabilities and potential whilst remaining uncertain about the process factors which determine how this technology may be applied and adopted effectively. Furthermore, much of current expert systems research work and literature addresses these issues from the viewpoint of the supplier or donor whilst overlooking the importance of human and organisational perspectives which shed light on the means of delivery and take-up within the recipient organisation . The paper, the second of two that look at expert systems innovation in manufacturing, argues for greater consideration of the characteristics, processes and mechanisms of technology transfer. It defines a new conceptual basis for technology transfer which stresses a ‘needs-driven’ process of change; this highlights the importance of context as well as content in expert systems transfer and implementation. From this, a management framework is outlined and is used to rationalise the transfer problems and needs described in the first paper following a survey of 145 manufacturing users. It is also shown how this framework may be used to understand more about the multi-level and multi-dimensional needs and effects of technology induced change and therefore how it may be used to help senior management strategically plan and co-ordinate expert systems programmes in their organisations.

Expert systems in manufacturing. Part 1: A users' perspective on expert-systems innovation

Abstract The development of applications with proven benefits, the availability of better development methodologies and tools, realism about what expert systems are capable of, and the integration of expert systems into mainstream information technology are all factors that, in the 1990s, will promote increased exploitation of this technology in the manufacturing sector. Despite these developments, however, there still remains some uncertainty as to precisely how expert systems are being used in manufacturing other than in the ‘show-case’ and large-scale demonstration systems, and in the more general attempts to disseminate selected companies' experiences in developing applications in an attempt to define ‘best practice’. Further, little attention has been paid to the managerial context and human and organizational processes involved in expert-systems innovation. The paper is one of two that review the management of expert-systems technology in manufacturing. It begins by evaluating current experiences with expert systems through a study of 145 manufacturing companies in the UK, from which an agenda of business, technical and managerial issues is raised. The analysis highlights the importance of human and organizational perspectives in the understanding of why expert systems succeed, or indeed fail, and it points to the need for greater attention to be paid to the process issues of innovation that help companies to define and manage appropriate development pathways in their organization — appropriate in the sense that they are meaningful within a specific organizational context, and adaptable given a company's specific needs and constraints. The second paper extends these arguments to a consideration of the wider processes of technology (and knowledge) transfer, and it develops a management framework to facilitate successful innovation in expert systems, and, more importantly, to enable desirable organizational change to take place.

Object-oriented expert system architectures for manufacturing quality management

Abstract The use of expert systems in manufacturing is steadily increasing. The majority of these systems are designed to perform process control or to diagnose process malfunction. Though quality control is generally not an explicit development goal, a number of manufactures have realized quality improvements from the use of expert systems. The premise of this paper is that, instead of accepting quality improvements as a windfall from the development of intelligent systems, manufacturers could benefit from expert systems designed to support quality management activities. General object-based architectures for expert systems developed from the principles of two proven quality management methods—Quality Function Deployment and Quality Planning—are proposed.

Applications of expert systems in manufacturing: A case study

This paper describes the practical experience gained in a project the aim of which was to introduce expert system technology into a manufacturing organisation. The project involved the development of an expert system shell and a knowledge base for fault diagnosis in numerically controlled machine tools. Particular emphasis is placed on the implementation strategy and the difficulties encountered during the course of the project. Factors discussed include management support and availability of technical expertise. Current limitations of expert system technology with respect to engineering applications are also discussed.

Evaluation of Manufacturing Expert Systems: Framework and Model

ABSTRACT A great deal of attention has been given to the use of expert systems in solving manufacturing problems by software development experts as well as application experts. However, the evaluation of expert systems in manufacturing applications has received very little attention in the literature. Whether or not an expert system is justified for a particular manufacturing environment depends on the expert system's effectiveness on both the manufacturing problem and the problem environment. An expert system may be evaluated according to the effectiveness of its ability to solve problems (interpret, predict, diagnose, design, plan, monitor, debug, repair, instruct, and control), interface with users, and handle knowledge (learn, represent, induce, and retrieve). It may also be evaluated on other aspects such as expandability, responsiveness, or simply its costs. However, it is difficult to measure all the costs and benefits of an manufacturing expert system and to perform a traditional economic analysis...

The Boston University Manufacturing Expert System (BUMES)

Manufacturing engineering involves the processes and equipment required to design, analyze, fabricate, and test products. The transition from an engineer's first sketch to a finished, machined part is traditionally a long, expensive, difficult path. This path includes a variety of separate software solutions to individual subproblems. Together, these separate solutions raise many confusing issues of capability, compatibility, and design integrity. This paper presents the design and implementation of a fully integrated solution to this problem. This system enables a designer to sketch a part graphically, and immediately have it machined. Because this rapid-prototyping system was designed as an integrated solution, it allows the process rules to be available up-front in the part design stage, so that unmanufacturable design features are identified immediately, as the designer attempts to add them to the part. This rapid-prototyping capability also addresses the need to modify the part by changing its dimensions or its features. Design changes and subsequent machining are rapid because of the use of relational geometry, which remembers the geometric relationships between the part's geometric elements, so that if some are changed, all can be adjusted automatically. The prototype Boston University Manufacturing Expert System (BUMES) was designed and implemented using the Expert System Generator (ESG) CASE tool, in APL2.