2014Management and Production Engineering ReviewOpen access

Design for manufacturability in virtual environment using knowledge engineering

Julian Jakubowski, Jozef Peterka

Open full text 15 citations

Abstract

Abstract Design for manufacturing (DFM) strategies help companies to develop new products that are feasible to manufacture. In the early stages of design all engineering activities are initiated in computer aided systems. When the design is finished, the process of manufacturing and production planning begins. Issues often occur at this point because two teams, designers and manufacturers, have been working separately. The resulting question is: ‘how can Knowledge Engineering (KE) be used effectively to enhance manufacturability during early design?’ Even if the most complex geometrical product can be realized using today’s technologies such as rapid prototyping it is only true in unit production. In lot and mass production where CNC machines are used, complex geometry causes a number of difficulties. So it is important to investigate the project carefully in the early design stage from the point of view of whether it will be possible to manufacture.

Open-access reader

About this research paper

What this paper is about

Abstract Design for manufacturing (DFM) strategies help companies to develop new products that are feasible to manufacture. In the early stages of design all engineering activities are initiated in computer aided systems. When the design is finished, the process of manufacturing and production planning begins. Issues often occur at this point because two teams, designers and manufacturers, have been working separately. The resulting question is: ‘how can Knowledge Engineering (KE) be used effectively to enhance manufacturability during early design?’ Even if the most complex geometrical product can be realized using today’s technologies such as rapid prototyping it is only true in unit production. In lot and mass production where CNC machines are used, complex geometry causes a number of difficulties. So it is important to investigate the project carefully in the early design stage from the point of view of whether it will be possible to manufacture.

Why it matters

OpenAlex reports 15 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Abstract Design for manufacturing (DFM) strategies help companies to develop new products that are feasible to manufacture. In the early stages of design all engineering activities are initiated in computer aided systems. When the design is finished, the process of manufacturing and production planning begins. Issues often occur at this point because two teams, designers and manufacturers, have been working separately. The resulting question is: ‘how can Knowledge Engineering (KE) be used effectively to enhance manufacturability during early design?’ Even if the most complex geometrical product can be realized using today’s technologies such as rapid prototyping it is only true in unit production. In lot and mass production where CNC machines are used, complex geometry causes a number of difficulties. So it is important to investigate the project carefully in the early design stage from the point of view of whether it will be possible to manufacture.

Key concepts: Design for manufacturability, Manufacturing engineering, Concurrent engineering, Product design, Engineering design process, Production (economics), Engineering, Virtual prototyping

Related papers

Back to paper searchBrowse research topicsOriginal source
Design for manufacturability in virtual environment using knowledge engineering — Research Paper | ScholarLens