The International Journal of Advanced Manufacturing Technology

Plenert, Gerhard

doi: 10.1007/BF01178956pmid: N/A

Ko, Tae; Cho, Dong

doi: 10.1007/BF01178957pmid: N/A

An adaptive signal processing scheme that uses a low-order autoregressive time series model is introduced to model the cutting force data for tool wear monitoring during face milling. The modelling scheme is implemented using an RLS (recursive least square) method to update the model parameters adaptively at each sampling instant. Experiments indicate that AR model parameters are good features for monitoring tool wear, thus tool wear can be detected by monitoring the evolution of the AR parameters during the milling process. The capability of tool wear monitoring is demonstrated with the application of a neural network. As a result, the neural network classifier combined with the suggested adaptive signal processing scheme is shown to be quite suitable for in-process tool wear monitoring

Liu, Cheng-liang; Tsai, Wen-ching

doi: 10.1007/BF01178958pmid: N/A

An electromagnetic chuck is typically employed for surface grinding processes and is a convenient workholding device for ferro-magnetic materials. However, the electromagnetic chucking force varies with magnetic pole arrangement, workpiece mounting position, thickness, surface roughness, and so on. This paper attempts, through the analysis of a series of experiments, to determine the parameters in uencing the attraction forces of the electromagnetic chuck and help efficient chucking work. The final remarks include suggestions for useful applications of the electromagnetic chuck.

Champati, Supratik; Lu, Wen; Lin, Alan

doi: 10.1007/BF01178959pmid: N/A

This paper addresses the methodology development for achieving one of the important functions in automated process planning: automated determination of sequence of machining operations for prismatic parts containing various types of form features. A framework of using the case-based reasoning approach to support learning capability in operation sequencing is first proposed. The methodology to accomplish various issues in case-based operation sequencing is then discussed. In particular, the following issues are considered: 1. Representation of operation sequencing cases. 2. Indexing and retrieval of operation sequencing cases. 3. Adaptation of operation sequencing cases. Finally, the implementation issues are addressed and the learning functions of the intelligent operation sequencing system are demonstrated.

Huang, Hsin-Hao; Wang, H.

doi: 10.1007/BF01178960pmid: N/A

This paper discusses a machine fault diagnostic system which integrates three techniques: 1. An autoregressive model, which compresses digitised vibration signals and preserves the information carried in the original signal. 2. A supervised artificial neural network for fault classification. 3. A fuzzy logic-based “hypothesis and test” program, which, when the artificial neural network fails to provide any suggestion, is able to provide the human diagnostician with some initial “educated” guesses of machine conditions.

Finucane, M.; Black, I.

doi: 10.1007/BF01178961pmid: N/A

This paper covers the CO2 laser cutting of stained glass using a Ferranti MF400 CNC laser cutting machine. The report examines the various laser cutting parameters required to generate a cut surface in glass which will require minimal post-treatment to be carried out, and also investigates the degree of geometrical intricacy that can be attempted, together with the associated limitations, in cutting 2D glass components. The experimental procedure used to obtain the necessary information for a preliminary database on the laser cutting of stained glass is also detailed. Finally, the implications and applications of the investigative work are examined for commercial situations through construction of a simple 2D test artefact.

Mattila, Markku; Perälä, Maarit; Vannas, Vesa

doi: 10.1007/BF01178962pmid: N/A

Safety improvements of Flexible Manufacturing Systems (FMSs) are improving usability of the system usability and also the competitiveness of the manufacturing. The aims of this study were 1) to analyze the deficiencies in and the risks of flexible manufacturing system (FMS) implementations 2) to clarify whether the systems meet the demands of safety standards and 3) to suggest safety system improvements. The study was made by using the Safety Analysis for Production Automation and the Safety Checklist for FMSs. The data were gathered by interviewing key managers and workers employed by 22 Finnish companies with FMS implementations. The study showed that although the companies considered the FM systems as one of their safest functions in the workshops, many of the systems do not fulfill the most common requirements of the safety standards. The requirements were met by 70% of the targets studied. Installation and maintenance functions best meet these requirements, whereas the layout of the systems and their mechanical structure were the most poorly designed areas. Especially poor were the safety and ergonomics of the loading/unloading stations. This paper presents additional information about the deficiencies found in the FM-systems and companies' involvement in them. The results shed new light on safety and ergonomic aspects to be considered in designing and using FM-systems. The data can be used to help industry meet safety demands and to improve the efficiency of new FMS implementations.

Massotte, Pierre

doi: 10.1007/BF01178963pmid: N/A

Recent works have shown that well-known models used for the analysis of human behaviour, in economics and in production—distribution contain unsuspected regimes of deterministic chaos. This paper is intended to study and analyse such behaviour in manufacturing and assembly shops.