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This research was conducted to study benefits of a concept, known as lean manufacturing, which elicits organizations to do more with less effort, time, space, and equipment by eliminating waste. Because lean implementation involves finances, dedication, and cultural change in business, there is a need to assess a company's lean initiative.

A comprehensive lean assessment tool is designed targeted for use by manufacturing companies. Research of lean principles and practices was conducted through lean organizations, trade publications, manufacturing web sites, professional articles, textbooks, lean exhibitions, and non‐profit lean organizations.

This led to the development of a lean survey questionnaire delivered to 143 lean companies and lean consultants for authentic input. Based on the response, survey participation met a goal of 95 percent accuracy with 15 percent error. Completed surveys were compiled and analyzed for fundamental practices of lean organizations. Answers to the survey were assigned numerical values based on lean significance, and a lean assessment model was developed based on Excel. The lean assessment model was fine‐tuned and programmed to output a numerical and descriptive lean assessment grade. It was tested for soundness by inputting mock lean and traditional company answers into the model. Output results from the model correlated with the input.

Lean thinking philosophy and lean manufacturing methods and principles were exhaustively researched to make a successful lean organization. The research led to the development of a visual indicator, the Lean Thinking Management Wheel. This model to assess lean thinking manufacturing initiatives unique and has a great potential to use industry wide.

The purpose of this paper is to develop a tool design for assembly and disassembly using rating factors. Design engineers need an automated tool to effectively analyze the ease of assembly and disassembly of the products or subassemblies. A good assembly design helps in easier disassembly and thus makes it easier to service, repair and maintain. Reuse and recycling aspects are given importance in the present days due to environmental regulations. Designers now use the life cycle design of the products. This creates an environment for the successful application of design for manufacturing, assembly and disassembly tools. This paper addresses some of those issues.

The analysis of a product design for ease of assembly/disassembly depends largely on whether the product is to be assembled/disassembled manually, with automation or a combination of these. For example, the criteria for ease of automatic feeding and orienting are much more stringent than those for manual handling of parts. The new design for assembly/disassembly (DFA/DFD) evaluation tool explained here enables the designer to review the existing design. This paper examines the existing techniques in the area of DFA/DFD and suggests a new methodology based on rating factors. Excel is used to create the interface for the user. Other popular methods were examined such as Boothroyd-Dewhurst, Lucas. Access, reuse, removal, tool, task and time method and assembly score method (Poli) were used as a base for this study.

The end result of this research is a new approach linked to assembly/disassembly rating score.

The new DFA/DFD evaluation tool enables the designer to review the existing DFA and DFD difficulties.

Explains that the rapid growth of artificial intelligence techniques, especially neural networks and knowledge‐based systems, have paved the way for the development of an intelligent and real‐time manufacturing information system. By efficiently utilizing the specific domain representation in a production cell, an intelligent system can manage the complex issues concerning the structure and character of the product, goals of the manufacturing unit and provide production guidance accordingly. Addresses issues in manufacturing intelligence through two case studies that demonstrate the feasibility of a real‐time quality control in changing environmental conditions. The quality and the factor of acceptability are determined by the intelligent agent. These intelligent agents involve the use of an artificial neural network system and, in some cases, a knowledge‐based system to control and operate, in real‐time, the functions of an inspection process in manufacturing. Addresses the design issues of interest, especially setting up global routines which can be used in a common platform to control a machine tool, interpret the sensor inputs, monitor the quality of products, and take corrective actions on a real‐time basis.