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Traditional machining centre selection methods may not guarantee a cost effective solution. Properly trained back‐propagation artificial neural network (BPANN) tend to select reasonable machining centres when presented with machining parameters that they have never seen before. The aim of this paper is to demonstrate the applicability of artificial neural networks (ANNs) to machine centre selection problems.

A three‐layer feedforward back‐propagation supervised training approach is selected to address the machining centre selection problem and demonstrated its potential through an example. This is intended to help readers understand implications on manufacturing system design and future research.

Very limited studies attempted the machining centre selection problem. Feedforward ANN approach has been applied to a wide variety of manufacturing problems. Neural networks have training capability to solve problems that are difficult for conventional computers or human beings. The developed BPANN model has potential to solve the machine centre selection problem with notable consistency and reasonable accuracy.

The BPANN model is an innovative approach fundamentally based on artificial intelligence, which is not directly visible to the user, but is able to solve through a simpler and supervised feedforward back‐propagation training process. The model consists of an input layer, a hidden layer and an output layer. The 18 neurons fixed in the input layer are same as the set of machining centre parameters which are taken directly from the machine tool manufacturer's catalogues. Evidently the proposed three‐layer ANN model has the capability of solving the machine centre selection problem with three hidden neurons for threshold level of 0.9, noise level of 0.05 and tolerance of 0.01.

The work size, weight, travel range, spindle speed range, horse power, feed, accuracy, tool magazine and price are used as machining centre selection parameters. Machining centres' information in the form of 24 patterns along with the desired machining centres' were used to train and test the network.

This paper presents an Internet‐based virtual machining system which applies virtual manufacturing technology to machining processes of CNC machining center. The system is implemented to execute digital machining and verification, to transmit the NC code data to related machining centers after confirming the properness of virtual machining, and to manipulate the machine through the Internet. Also, this research proposes a basic structure that can monitor the status of machines via the Internet. By applying simulation techniques for machining processes, a simple manipulation and monitoring system of machining centers is realized. This entire system is constructed by adopting the latest information technology such as object‐oriented method, middleware, Internet programming, and client‐server structure.

Cellular manufacturing is the organisation of manufacturing equipment based on the requirements of the product or component. Transition to cellular manufacturing generally requires reorganisation of existing equipment. It is likely that the existing equipment alone is not suitable for a cellular layout. During the cell planning and design phase equipment investment analysis is important to identify equipment needs. Transition from job shop production to cellular production is detailed. Cell formation and cell evaluation techniques are provided to assist in equipment procurement decisions. In particular, a structured procedure and analytical tools are given to evaluate fully the cellular system to identify appropriate equipment and methods. A case example is provided to explain the procedure.

The ideas expressed in this work are based on those put into practice at the Okuma Corporation of Japan, one of the world′s leading machine tool manufacturers. In common with many other large organizations, Okuma Corporation has to meet the new challenges posed by globalization, keener domestic and international competition, shorter business cycles and an increasingly volatile environment. Intelligent corporate strategy (ICS), as practised at Okuma, is a unified theory of strategic corporate management based on five levels of win‐win relationships for profit/market share, namely: ,1. Loyalty from customers (value for money) – right focus., 2. Commitment from workers (meeting hierarchy of needs) – right attitude., 3. Co‐operation from suppliers (expanding and reliable business) – right connections., 4. Co‐operation from distributors (expanding and reliable business) – right channels., 5. Respect from competitors (setting standards for business excellence) – right strategies. The aim is to create values for all stakeholders. This holistic people‐oriented approach recognizes that, although the world is increasingly driven by high technology, it continues to be influenced and managed by people (customers, workers, suppliers, distributors, competitors). The philosophical core of ICS is action learning and teamwork based on principle‐centred relationships of sincerity, trust and integrity. In the real world, these are the roots of success in relationships and in the bottom‐line results of business. ICS is, in essence, relationship management for synergy. It is based on the premiss that domestic and international commerce is a positive sum game: in the long run everyone wins. Finally, ICS is a paradigm for manufacturing companies coping with change and uncertainty in their search for profit/market share. Time‐honoured values give definition to corporate character; circumstances change, values remain. Poor business operations generally result from human frailty. ICS is predicated on the belief that the quality of human relationships determines the bottom‐line results. ICS attempts to make manifest and explicit the intangible psychological factors for value‐added partnerships. ICS is a dynamic, living, and heuristic‐learning model. There is intelligence in the corporate strategy because it applies commonsense, wisdom, creative systems thinking and synergy to ensure longevity in its corporate life for sustainable competitive advantage.

Production for Plenty. At a time when many established industrial exhibitions are struggling to survive, it is a bold step on the part of the Institution of Production Engineers to launch the first Production Exhibition and Conference which they hope will become an annual event. This will be an exhibition with an entirely new theme—one which the general public, as well as industry, are coming to know and appreciate as a force for the future in both their working and domestic lives.

BEAUMONT Machine Tool Co Ltd recently unveiled the new Matsuura FX‐5 high speed vertical machining centre for the first time in the UK at its new facility in Coalville, Leicestershire, following upon the inauguration of the company at a ceremony performed by Sir Hugh Cortazzi, Chairman of the Japan Society and former British Ambassador to Japan in the presence of Mr. Katsumi Sezaki, Minister Plenipotentiary of the Embassy of Japan and Councillor Guy Collis, Lord Mayor of Leicestershire. The Matsuura Machinery Corporation was represented by its founder Masanori Matsuura.

The purpose of this paper is to propose a general model for locating and clamping workpieces of complex geometry with two skewed holes under multiple constraints.

Numerous constraints related to application of the proposed model are discussed as prerequisite to design of fixture solution. Based on theoretical model, a fixture was designed and successfully tested in experimental investigation. Experimental results were also verified using FEM simulations.

This study showed that, opposed to conventional approach, novel solution results in significantly smaller fixture dimensions, while providing greater stability. Insertion of mandrels and supports element sub-assemblies into the workpiece holes significantly increases workpiece stiffness through an increased moment of inertia, while the internal support elements largely diminish the problem of thin wall deformation in the workpiece.

The fixture designed in this case was actually used in industrial application to accommodate a thin-walled casting of gearbox housing, where it proved to be a very stable framework. It can be used in industry without any major readjustments.

According to available literature, this work is the first successful implementation of a fixture solution in which the problem of multiple constraints is solved by attaching centering elements, support sub-assemblies, and other fixture elements to the internal workpiece walls, and then locating them in the second part of the fixture.

Contrasts functional layouts and cellular layouts with regard to the effects of set‐up time reduction and lot size on flow time and through‐put. The structural environment for the functional analysis is an efficient functional system with a staged sequence of four machine centers with unidirectional flow and no backtracking. The structural environment for the cellular analysis is a partitioned cell consisting of one machine from each of the four machine types with unidirectional flow and no backtracking. Simulation models produce robust results for eight lot size levels and one (functional model) and seven (cellular model) set‐up time reduction levels. The results contrast the effectiveness of the two manufacturing approaches under differing input conditions. Shows that the choice between the functional structure and the cellular structure significantly affects through‐put at lot sizes up to 55, while for lot sizes of 60 and above there is no significant effect. The study also confirms previous results regarding the effect of manufacturing structure choice on flow time.

Subtractive manufacturing process is the controlled removal of unwanted material from the parent workpiece for having the desired shape and size of the product. Several types of available machine tools are utilized to carry out this manufacturing operation. Selection of the most appropriate machine tool is thus one of the most crucial factors in deciding the success of a manufacturing organization. Ill-suited machine tool may often lead to reduced productivity, flexibility, precision and poor responsiveness. Choosing the best suited machine tool for a specific machining operation becomes more complex, as the process engineers have to consider a diverse range of available alternatives based on a set of conflicting criteria. The paper aims to discuss these issues.

Case-based reasoning (CBR), an amalgamated domain of artificial intelligence and human cognitive process, has already been proven to be an effective tool for ill-defined and unstructured problems. It imitates human reasoning process, using specific knowledge accumulated from the previously encountered situations to solve new problems. This paper elucidates development and application of a CBR system for machine tool selection while fulfilling varying user defined requirements. Here, based on some specified process characteristic values, past similar cases are retrieved and reused to solve a current machine tool selection problem.

A software prototype is also developed in Visual BASIC 6.0 and three real time examples are illustrated to validate the application potentiality of CBR system for the said purpose.

The developed CBR system for machine tool selection retrieves a set of similar cases and selects the best matched case nearest to the given query set. It can successfully provide a reasonable solution to a given machine tool selection problem where there is a paucity of expert knowledge. It can also guide the process engineers in setting various parametric combinations for achieving maximum machining performance from the selected machine tool, although fine-tuning of those settings may often be required.

Machine tending is the oldest of applications for the Industrial Robot, and is even more economically beneficial today than it was in 1960 when the first robot was installed at a die casting machine. Robots now serve many more types of machines and a number of recent applications are described. These include injection moulding machines, machining centres, CNC lathes, cylindrical grinders and press brakes. All these cases identify the key benefit of “lights out” operation. However, the absence of operators brings the problems of unscheduled stoppages going undetected until “the day shift arrives”. One answer discussed is remote monitoring by tele‐linking the machine to a control centre. Finally, a case study is described of a polishing cell for stainless steel sanitary and catering equipment in which the robots handle the parts as well as manipulate the polishing tools.