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Full-Text Articles in Engineering
The Management Of Change: A Case Study, Stephen A. Raper, Richard Neal Callahan
The Management Of Change: A Case Study, Stephen A. Raper, Richard Neal Callahan
Engineering Management and Systems Engineering Faculty Research & Creative Works
A literature review was conducted to identify some of the requirements for competitiveness and change that are being promoted by leaders in the manufacturing field. A survey was developed based on the literature review and was subsequently administered, via the case study method, at a midwestern US agricultural chemicals firm to determine the company's degree of compliance with the literature''s recommendations. To a large degree, the company complied with the requirements.
Neural Networks In Manufacturing: Possible Impacts On Cutting Stock Problems, Cihan H. Dagli
Neural Networks In Manufacturing: Possible Impacts On Cutting Stock Problems, Cihan H. Dagli
Engineering Management and Systems Engineering Faculty Research & Creative Works
The potential of neural networks is examined, and the effect of parallel processing on the solution of the stock-cutting problem is assessed. The conceptual model proposed integrates a feature-recognition network and a simulated annealing approach. The model uses a neocognitron neural network paradigm to generate data for assessing the degree of match between two irregular patterns. The information generated through the feature recognition network is passed to an energy function, and the optimal configuration of patterns is computed using a simulated annealing algorithm. Basics of the approach are demonstrated with an example.
Possible Applications Of Neural Networks In Manufacturing, S. Lammers, Cihan H. Dagli
Possible Applications Of Neural Networks In Manufacturing, S. Lammers, Cihan H. Dagli
Engineering Management and Systems Engineering Faculty Research & Creative Works
Summary form only given. An examination is made of the potential of neural networks and the impact of parallel processing in the design and operations of manufacturing systems. After an initial discussion on possible areas of application, an approach that integrates artificial intelligence, operations research, and neural networks for the solution of a scheduling problem is examined