Computer Integrated Manufacturing Systems Research Articles

Design and implementation of decentralised supervisory control for manufacturing system automation

Supervisory control theory, which was first proposed by Ramadge and Wonahm, is a well-suited control theory for the control of complex systems such as semiconductor manufacturing systems, automobile manufacturing systems, and chemical processes because these are better modelled by discrete event models than by differential or difference equation models at higher levels of abstraction. Moreover, decentralised supervisory control is an efficient method for large complex systems according to the divide-and-conquer principle. This article presents a solution and a design procedure of supervisory control problem for the case of decentralised control. We apply the proposed design procedure to an experimental miniature computer-integrated manufacturing (CIM) system. This article presents the design of fourteen modular supervisors and one high-level supervisor to control the experimental miniature CIM system. These supervisors are controllable, non-blocking, and non-conflicting. After the verification of the supervisors by simulation, the collision avoidance supervisors for automated guided vehicle system have been implemented to demonstrate their efficacy.

Recognition of Distorted CAD Objects using Neural Networks

uses of features have been considered to be the technology which bridges the gap between Computer aided design (CAD) and Computer aided manufacturing (CAM) in the CIMS (Computer Integrated manufacturing systems).Active research in the last two decades has resulted in a number of recognition techniques like rule based, graph matching, volume decomposition, hint based, neural network, etc. This paper presents the development of distorted CAD objects recognition system. A well-known multi- layer Perceptron (MLP) neural network with backpropagation learning algorithm is chosen for its fast processing time and its good performance for feature recognition problems. Learning systems that learn from previous experiences and/or provided examples of appropriate behaviors, allow the people to specify what the systems should do for each case, not how systems should act for each step. The recognition system is programmed in C++.

A Modified Genetic Algorithm(GA) for Optimization of Process Planning

Computer-aided process planning (CAPP) is an important and complex in the computer integrated manufacturing system(CIMS). The expression methods of process knowledge based on manufacturing feature is established based on the analysis of characteristic of process knowledge. According to the constraints mong process knowledge, decision space of process planning based on process constraints is constructed which improved search efficiency of GA. In allusion to the uncertainty of decision of process planning, the multi-objective optimization function is established, and a GA is applied to optimization of process planning. Process planning is optimized using the reasonable coding strategy, fitness function, selection, crossover and mutation algorithm, etc. An case is offered to illustrate the process of optimization of process planing based on GA.

A New Approach for Automation of Locating Planning of Workpiece

Fixtures are used to locate and constrain firmly a workpiece during machining operation. Flexible and efficient fixturing has become an important issue in flexible manufacturing systems and computer integrated manufacturing system. Locating planning is the basis of the fixturing design, which has a direct influence on the quality of the clamping scheme and the machining quality of workpiece. This paper presents a new approach for locating planning of workpiece. Firstly, it will automatically select the primary locating surfaces with consideration of 5 influence factors: constraint freedoms, surface feature, valid locating area, tolerance relationship and surface roughness. Then the other locating surfaces are determined by retrieving similar workpieces under the guideline of 4 locating methods which will make the best of already available locating planning. Finally the optimal locator layout is fast achieved with GA with the goal of minimal locating tolerance.

Agent Based State Monitor Framework for RP Manufacture Process

Providing web service interface in the function layer is becoming a technology trend. Recent research in computer integrated manufacturing system is focused on integrating this with automation technology. This paper presents an integrated framework for monitoring the state change during rapid prototyping and manufacture (RP&M) processes. Web service interface is exposed in the device control layer and grouped into an aggregation service in the upper layer. In order to wrap the heterogeneous structure of different type of Rapid Prototyping (RP) device and systems, an agent based software framework is developed to reduce the complexity of data transmission and provide an isomorphic web service interface for status-monitoring and event-apperceiving. Compare to the OPA UA specification this framework provides a more simple realization in RP&M process.

Learning IF–THEN priority rules for dynamic job shops using genetic algorithms

Performing complex, informed priority rules might pose a challenge for traditional operator-driven systems. However, computer-integrated manufacturing systems may significantly benefit from the complex, informed rules such as state-dependent priority rules. A state-dependent priority rule can be defined as a list of IF–THEN priority rules that will be performed if certain system conditions are satisfied. Here, we propose a genetic algorithm based learning system for constructing interval-based, state-dependent priority rules for each interval of queue lengths in dynamic job shops. Our approach builds interval based state-dependent priority rules pairing the priority rules with the intervals of queue lengths, and determines priority rules and their corresponding length of intervals for a given objective. A genetic algorithm is developed for matching queue length intervals with appropriate priority rules during simulation. A system simulation evaluates the efficiencies of interval based state dependent priority rules. The experiments show that interval-based state dependent priority rules obtained by the proposed approach considerably outperform the priority rules including shortest processing time (SPT), minimum slack time (MST), earlier due date (EDD), modified due date (MDD), cost over time (COVERT), and critical ratio (CR) for total tardiness for most of the problems.

Computer-integrated manufacturing and high performance work system: the case of Taiwan

This study investigates the relationships between computer-integrated manufacturing (CIM) and high-performance work system (HPWS) that can arguably improve human capital in the firm and enhance the effectiveness of these advanced manufacturing technologies. Our data were drawn from two surveys of Taiwanese manufacturing establishments in 1998 and 2005. Results showed that high-degree CIM was positively associated with the practices of the each HR practice and HPWS, including high pay level, rigorous selection, extensive training, developmental performance management, performance- and competency- based rewards as well as employee stock ownership.

An elastic force based collision avoidance method and its application to motion coordination of multiple robots

A key contribution of robots to a manufacturing system is flexibility and automation. The robots can handle part batches of varying size and mix and can adapt to process variations and uncertainties in the working environment. This paper proposes a method for the collision-free motion coordination of multiple robots in a common working environment. The method uses an improved elastic force based method for collision avoidance. For the motion coordination of multiple robots, prioritisation-and-avoidance is used. Priority is assigned to each robot with a robot of lower priority avoiding the robots of higher priority. Without priority, every robot takes pains to avoid all the other robots. This degrades the overall performance of the coordinated motion. In addition, priority allows a robot with an urgent job to perform its job quicker. For collision avoidance, elastic force as well as potential field force is used. Compared with the method using only the potential field force, the robot can keep its configuration while avoiding other robots. Moreover, by adjusting the elastic force, task-consistent motion is possible. This method is tested by simulation and results in a smooth and adaptive coordination in an environment with different types of robots. Also the proposed method is compared with a method using the conventional elastic strip based method. The method can be used to coordinate the motion of multiple robots in a common working environment of a CIM system without interference.

Implementation and assessment of computer integrated manufacturing in systems engineering education

AbstractThis article is concerned with the presentation of consolidation of Industrial Engineering (IE) and Automation and Control Engineering (ACE) under Systems Engineering frame while demonstrating how Computer Integrated Manufacturing (CIM) systems can be a sufficient for the proper perspective on the topic of concern, Systems Engineering practical example conforming to this integration. Systems Engineering involves with finding integrated solutions to problems that are of large scale and scope, which are in the nature of cross and inter‐disciplinary. The article addresses to certain details, identity, and Systems Engineering program at Yeditepe University, Istanbul, Turkey which consolidates IE, and ACE. CIM system can be considered as a typical Systems Engineering topic of concern since its hierarchical structure and sufficient complexity as well as being tangible and scalable for the purpose of education. CIM philosophy can be viewed as the peak of ongoing effort in the application of automation in the manufacturing and it encapsulates the total manufacturing enterprise through the use of integrated systems and data communications coupled with new managerial philosophies that improve organizational and personnel efficiency. The manufacturing of a simple toy car in the CIM lab is presented as a case study to demonstrate exploiting the concepts and notions given in the IE and ACE. © 2009 Wiley Periodicals, Inc. Comput Appl Eng Educ 18: 117–129, 2010; Published online in Wiley InterScience (www.interscience.wiley.com); DOI 10.1002/cae.20215

Extraction of manufacturing information from design-by-feature solid model through feature recognition

Feature recognition is the key to the computer-aided design (CAD) and computer-aided manufacturing (CAM) integration to build a computer-integrated manufacturing system. There are two approaches to CAD feature recognition: platform-dependent and platform-independent. In the platform-independent approach, the part’s geometrical data are extracted from a neutral file such as DXF, IGES, or STEP. In contrast, the platform-dependent approach extracts the information of the design features directly from a design-by-feature solid model through the object-oriented model of a part. This paper explains a platform-dependent approach which is implemented to translate design features into manufacturing information. This approach begins with simplification using the suppression of fillets, and clustering non-intersecting design features is done. Then, the rule-based method is employed in order to recognize machining features. Finally, the needed manufacturing information such as tool accessing direction, dimensions, material removal regions, and geometrical and topological data is recognized. The application of the proposed system would be exhibited in generating machine path code for rapid prototyping and CNC machines and providing a database for computer-aided process planning. The proposed system was implemented on Autodesk Inventor and successfully tested for many complex 3D models.

Hierarchical Scheduling of Mobile Robots in Production-Transportation Supply Chains

In this paper we propose a decomposition approach that hierarchically integrates the batching and local search heuristics in manufacturing scheduling. The problem comprises two main interrelated stages embedded in any production-transportation supply chain, namely (i) scheduling processing of raw materials and robot's transportation operation within each individual cell, and (ii) scheduling of transportation and distribution of batches of semi-finished products between cells. Several efficient heuristic algorithms are proposed. This work has been motivated by a real-life problem of production planning for a CIM system for manufacturing of multi-component products served by robots.

Yeditepe University computer integrated manufacturing studies

AbstractThe role of manufacturing enterprises in developing countries is more significant for economic prosperity than the developed countries since financial institutions are not well established. Today, the capability of producing high quality products with shorter delivery times and the ability to produce according to the diverse customer requirements have become the characteristics required for order‐qualifiers for manufacturing industries. Computer Integrated Manufacturing (CIM) systems have become the backbone of modern manufacturing paradigm for not only being profitable but also staying in business at any corner of the world. In this respect academies play a prominent role to produce well equipped engineers being ready to take the challenge of maintaining and improving CIM systems. This paper is an effort to illustrate a prototype design and manufacturing project with necessary improvements in an educational CIM laboratory by addressing to the courses in the curriculum of Systems Engineering at Yeditepe University. Following to the insightful introduction to the laboratory facilities, the design, simulation and implementation of the prototype are presented. The results obtained are discussed from system engineering education perspective. © 2008 Wiley Periodicals, Inc. Comput Appl Eng Educ 17: 1–12, 2009; Published online in Wiley InterScience (www.interscience.wiley.com); DOI 10.1002/cae20144

Using a system-diagnostic approach to solve information and operation issues in shop-floor integration systems

In order to improve the operation performances of enterprises, managers generally introduce relevant information systems to management, but as the production and operating procedures of enterprises differ, so the composition of the necessary system will also be different. Most research discusses system models and modules in a computer integrated manufacture system (CIMS), but less likely to discuss the problem and settlement method to actually implement. This research focuses on the shop-floor integration system (SFIS) as a real time management system using neural network technology to do the system diagnosis against system operational errors. Furthermore, the approach will discuss and improve the system efficiency by analyzing the questionable information detected. A real case is provided to demonstrate the effectiveness of the presented approach.

Editorial to 1st International & 22nd AIMTDR

This special issue of IJAMT consists of some select papers of the 1st International and 22nd All India Manufacturing Technology Design and Research (AIMTDR) conference held at Indian Institute of Technology (I.I.T.) Roorkee (India) during Dec.21–23, 2007. Let me give a very brief history of these AIMTDR conferences. The first AIMTDR conference was held at Jadavpur University, Calcutta in the year 1967. Initially, this conference used to be held every year till 1970 but later on the National Advisory committee (NAC) of AIMTDR decided to hold it every alternate year. The first biennial conference was held at University of Roorkee (now, I.I.T. Roorkee) in 1971. Initially, the acronym AIMTDR stood for “All India Machine Tool Design and Research” which was some time in the late 1980s changed to “All India Manufacturing Technology Design and Research” retaining the same AIMTDR acronym. With increasing participation from abroad and to further encourage this trend, a new dimension to the AIMTDR Conference has been added in its latest venture and it has been designated as the 1st International & 22nd AIMTDR Conference. This new name made it possible to include research activities in this conference related to various manufacturing technologies such as casting, forging, machining, inspection, metrology, etc. Not only this, the conference organizers started encouraging research activities related to the newly evolving areas in manufacturing systems and technologies, namely, Computer Integrated Manufacturing Systems, Flexible Manufacturing Systems, Cellular Manufacturing, Just-In-Time, Concurrent Engineering, and so on. In the past one decade or so, many new areas have rapidly emerged especially under the umbrella of nano-technology including μand nano-fabrication, μto nano-finishing, micromachining, μ-forming, μ-forging, and similar other technologies. Computational Manufacturing Engineering (CME) too has been an area of research interest of many researchers since long time. AIMTDR conference also includes research papers related to modeling and simulation of manufacturing processes. Some of the very new areas that are being covered by the AIMTDR conference include Web Manufacturing, Supply Chain Management, Green Manufacturing, Intelligent Manufacturing Systems, and similar others. Manufacturing has been benefited significantly from the recent developments in the areas such as IT, microelectronics, new materials, advanced sensors, and actuators. Computer support in manufacturing covering design, process control, and data transfer has enabled manufacturing to scale new heights leading to globalization and resource optimization. An increased awareness of the environment and the need to conserve energy has led to new developments in this field. International competition with customer focus has brought out the importance of excellence in quality, agility, and cost factors in manufacturing. Environmentally sustainable manufacturing technologies, increased customer expectations, and rapid response to customers need call for constant technological innovations in manufacturing. AIMTDR conferences have been covering many such areas for discussion and publication of research papers thus making it a dynamic conference changing with time to capture the needs of the user industries. This feature of the conference was well reflected in the contributed papers submitted for presentation in the 1st International and 22nd AIMTDR Conference held at Int J Adv Manuf Technol (2008) 38:489–490 DOI 10.1007/s00170-008-1590-6

Virtual-reality-based information requirements analysis tool for CIM system implementation: a case study in die-casting industry

A virtual-reality-based information requirement analysis tool (VR–RA tool) has been developed for an existing methodology, in order to capture and represent the enterprise information requirements of computer integrated manufacturing (CIM). The present paper describes the operational aspects of the existing methodology in VR–RA and introduces the developed VR–RA tool, which can be used by system analysts for determination of information requirements. A virtual manufacturing environment for matching the physical and the information model domains is utilized to delineate the information system requirements of CIM implementation. A set of rules and a knowledge base is appended to the virtual environment to remove any inconsistency that could arise between the material and the information flows during the requirement analysis. An experimental case study has been carried out in a firm in the die-casting industry in order to demonstrate the features and the potential industrial application of the VR–RA tool outlined in the current paper.

Selection of lean manufacturing systems using the PROMETHEE

PurposeIn recent years, many manufacturing companies are attempting to implement lean manufacturing systems (LMS) as an effective manufacturing strategy to survive in a highly competitive market. Such a process of selecting a suitable manufacturing system is highly complex and strategic in nature. The paper aims to how companies make a strategic decision of selecting LMS as part of their manufacturing strategy, and on what basis such strategic decisions are made by the managers.Design/methodology/approachA case study of a small‐ and medium‐sized enterprise is presented, in which the managers are contemplating on implementing either computer integrated manufacturing systems (CIMS) or LMS. To supplement the decision‐making process, a multi‐criteria decision making (MCDM) model, namely, the preference ranking organisation method for enrichment evaluations (PROMETHEE) is used to analyse how it will impact the stakeholders of the organisation, and the benefits gained.FindingsAn extensive analysis of PROMETHEE model revealed that LMS was the best for the given circumstances of the case.Research limitations/implicationsThe same problem can be extended by incorporating the constraints (such as financial, technical, social) of the organisation by utilising an extended version of PROMETHEE called the PROMETHEE V. Since, a single case study approach has been utilised, the findings cannot be generalized for any other industry.Practical limitations/implicationsThe methodology of PROMETHEE and its algorithm has been demonstrated in a detailed way and it is believed that it will be useful for managers to apply such MCDM tools to supplement their decision‐making efforts.Originality/valueAccording to the authors’ knowledge there is no paper in the literature, which discusses the application of PROMETHEE in making a strategic decision of implementing LMS as a part of an organisation's manufacturing strategy.

A multi-criteria decision-making model for the justification of lean manufacturing systems

In recent years, organisations are facing stiff competition in both domestic as well as global markets due to the impact of globalisation and rapid development of technologies. To achieve a competitive advantage over other firms in these circumstances, some managers’ attempt to transform their organisation by implementing highly successful management philosophies proposed by Japanese and Western management gurus, such as Just-In-Time (JIT), Total Quality Management (TQM), Total Productive Maintenance (TPM), Six-Sigma (SS), Lean Manufacturing Systems (LMS) etc. On the other hand, some managers’ bank on highly sophisticated, technology based systems such as Flexible Manufacturing Systems (FMS), Computer Integrated Manufacturing Systems (CIMS), Information Systems (IS) that enable e-business through the use of software packages for Enterprise Resource Planning (ERP), Supply Chain Management (SCM), Customer Relationship Management (CRM) etc. But an intriguing question that has not been answered completely is: ‘how do managers make a decision of implementing a ‘management based and people oriented philosophy and practice’ (say LMS) or a technically sophisticated system (say CIMS)?’ Implementing such massive change management programmes require a strong justification for the managers to convince the top management, as it involves huge investment and creates a longstanding impact on various resources. But such justification problems are quite complex. Traditional techniques cannot be applied as they do not account for intangible factors and benefits offered, which necessitate the use of Multi-Criteria Decision-Making (MCDM) models. Hence in this paper, an attempt has been made to demonstrate the application of a MCDM model, namely, the Performance Value Analysis (PVA) to analyse the alternatives (i.e., change management programmes) based on its impact on various performance measures of an organisation. A detailed algorithm of the PVA model is demonstrated using a case situation, which showed that LMS is the best for the given situation, as it results in overall improvement in the performance of the organisation.

Efficient mechanism development for multirobot coordination

Mobile robots are indispensable in computer integrated manufacturing systems which involve flexible automation. Hence robot teams working together on tasks should be made to share the workload efficiently in a cost effective manner. The current scenario is handicapped as it considers only the distance between the robots and the targets, and not much importance is given to the utilisation of the robots. This drawback can be eliminated with the adoption of the proposed methodology. This work formulates a mathematical model and presents a novel approach for multirobot coordination using combinatorial auctions in order to maximise robot utilisation while minimising incurred costs. For coordination tasks robots are considered as bidders and targets are considered as the items to be bid. A simulator has also been created for the same using Visual Basic System. The proposed mechanism is illustrated with a suitable example and the robustness of the mechanism is validated.

Collaborative manufacturing process planning for distributed integration in tooling industry

Computer-Integrated Manufacturing (CIM) system plays an important role in helping manufacturing companies move towards enterprise-wide automation in achieving competitive advantages. Manufacturing process planning plays a significant role by providing concurrent integration capabilities, from design to planning, scheduling and manufacturing. A concurrent manufacturing process planning architecture has been developed to support the integration of process planning with design, manufacturing, Capacity Planning and Scheduling (CPS) for tooling production. A prototype system based on this system architecture has been developed and tested in a tooling job shop, with satisfactory results.

Optimum Steelmaking Charge Plan with Unknown Charge Number Based on the Pseudo TSP Model

This paper presents a mathematical charge plan model of steelmaking-continuous casting (SCC) scheduling in the computer integrated manufacturing systems environment. Based on the analysis of the difficulty to solve the scheduling problem, a pseudo travel salesman problem model is presented to describe the scheduling model. By using this method, we can solve the optimum charge problem even without known the charge number, while other methods must know the charge number previously. To solve the problem, an improved discrete particle swarm optimization (DPSO) is presented. A new crossover probability is introduced into the DPSO algorithm, which is differed to that of the GA. Simulations have been carried and the results show that the pseudo travel salesman problem is very fit for describe the model. The computation with practical data shows that the model and the solving method are very effective.