A reliable turning process by the early use of a deep simulation model at several manufacturing stages

The future of machine tools will be dominated by highly flexible and interconnected systems, in order to achieve the required productivity, accuracy, and reliability. Nowadays, distortion and vibration problems are easily solved in labs for the most common machining operations by using models based on the equations describing the physical laws of the machining processes; however, additional efforts are needed to overcome the gap between scientific research and real manufacturing problems. In fact, there is an increasing interest in developing simulation packages based on "deep-knowledge and models" that aid machine designers, production engineers, or machinists to get the most out of the machine-tools. This article proposes a methodology to reduce problems in machining by means of a simulation utility, which uses the main variables of the system and process as input data, and generates results that help in the proper decision-making and machining plan. Direct benefits can be found in (a) the fixture/ clamping optimal design; (b) the machine tool configuration; (c) the definition of chatter-free optimum cutting conditions and (d) the right programming of cutting toolpaths at the Computer Aided Manufacturing (CAM) stage. The information and knowledge-based approach showed successful results in several local manufacturing companies and are explained in the paper.The work presented in this paper was supported in some sections within the project entitled MuProD-Innovative Proactive Quality Control System for In-Process Multi-Stage Defect Reduction- of the Seventh Framework Program of the European Union [FoF.NMP.2011-5] and UPV/EHU under program UFI 11/29. Thanks are given to Tecnalia, for collaboration in testing, and especially to Ainhoa Gorrotxategi and Ander Jimenez for the sound work in the project. Thanks to Gamesa Eolica and Guruzpe, for the time, technical advices, and efforts during the analysis in examples

Design & development of a simulation model to analyse scheduling rules in an FMS in a virtual manufacturing environment : a thesis presented in partial fulfilment of the requirements for the degree of Master of Technology in Manufacturing and Industrial Technology at Massey University

Due to the rapid changes in the needs of the customer for new products, the future manufacturing systems must cope with these changes. Hence, the need for the manufacturing systems to support these changes in the products with shorter lead times within a single manufacturing facility. The Virtual Manufacturing System (VMS) is one concept which can assist in meeting these demands. The VMS concept enables the manufacturing system designers to emulate and test the performance of the future manufacturing systems. This research has given an overview of the new concepts of Virtual Manufacturing Systems and Virtual Manufacturing in general. A Virtual Reality Software tool has been used to realise the VMS concept. A Virtual Manufacturing Environment representing a Flexible Manufacturing System (FMS) has been modelled. A simulation control language is employed for developing simulation control logics and decision making control logics for the development of the FMS model. The modelled FMS is implemented and tested through simulation experiments. The testing is done by analysing the traditional scheduling rules in a manufacturing facility. Average Machine Utilisation, Mean Flow Time, Average Queue Lengths and the System Production Rate are measured as the System Performance Measures for the evaluation of the scheduling rules. This research has identified that the Virtual Manufacturing Software is a powerful tool which can identify optimum configurations and highlight potential problems before a final and expensive manufacturing system is established physically

Multi-agent framework based on smart sensors/actuators for machine tools control and monitoring

Throughout the history, the evolutions of the requirements for manufacturing equipments have depended on the changes in the customers' demands. Among the present trends in the requirements for new manufacturing equipments, there are more flexible and more reactive machines. In order to satisfy those requirements, this paper proposes a control and monitoring framework for machine tools based on smart sensor, on smart actuator and on agent concepts. The proposed control and monitoring framework achieves machine monitoring, process monitoring and adapting functions that are not usually provided by machine tool control systems. The proposed control and monitoring framework has been evaluated by the means of a simulated operative part of a machine tool. The communication between the agents is achieved thanks to an Ethernet network and CORBA protocol. The experiments (with and without cooperation between agents for accommodating) give encouraging results for implementing the proposed control framework to operational machines. Also, the cooperation between the agents of control and monitoring framework contributes to the improvement of reactivity by adapting cutting parameters to the machine and process states and to increase productivity

Intelligent systems in manufacturing: current developments and future prospects

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS

Flexible data input layer architecture (FDILA) for quick-response decision making tools in volatile manufacturing systems

This paper proposes the foundation for a flexible data input management system as a vital part of a generic solution for quick-response decision making. Lack of a comprehensive data input layer between data acquisition and processing systems has been realized and thought of. The proposed FDILA is applicable to a wide variety of volatile manufacturing environments. It provides a generic platform that enables systems designers to define any number of data entry points and types regardless of their make and specifications in a standard fashion. This is achieved by providing a variable definition layer immediately on top of the data acquisition layer and before data pre-processing layer. For proof of concept, National Instruments’ Labview data acquisition software is used to simulate a typical shop floor data acquisition system. The extracted data can then be fed into a data mining module that builds cost modeling functions involving the plant’s Key Performance Factors

Energy efficiency in discrete-manufacturing systems: insights, trends, and control strategies

Since the depletion of fossil energy sources, rising energy prices, and governmental regulation restrictions, the current manufacturing industry is shifting towards more efficient and sustainable systems. This transformation has promoted the identification of energy saving opportunities and the development of new technologies and strategies oriented to improve the energy efficiency of such systems. This paper outlines and discusses most of the research reported during the last decade regarding energy efficiency in manufacturing systems, the current technologies and strategies to improve that efficiency, identifying and remarking those related to the design of management/control strategies. Based on this fact, this paper aims to provide a review of strategies for reducing energy consumption and optimizing the use of resources within a plant into the context of discrete manufacturing. The review performed concerning the current context of manufacturing systems, control systems implemented, and their transformation towards Industry 4.0 might be useful in both the academic and industrial dimension to identify trends and critical points and suggest further research lines.Peer ReviewedPreprin

Modeling a complex production line using virtual cells

This chapter presents modeling and simulation of a complex multistage multiproduct production line with four closed loop networks configuration, which also act as a virtual cell. This allows for a greater understanding of the functions within the production line through the simplification of the production flow with the addition of buffers between the cells. Virtual cells are crucial in this instance due to the dynamic configuration, which could help production system designers in optimizing the complex configuration of production