Computer Integrated Manufacturing Research Articles

Product life cycle information and process analysis methodology: Integrated information and process analysis for product life cycle management

In the manufacturing industry, collaborations between various departments, from planning, to the development and production phases, are becoming more and more important. Product life cycle management is the integrated management of information related to all phases of the product life cycle, from the analysis of customer requirements and product planning, to the maintenance and recycle phases. This makes product life cycle management one of the emerging strategies for organizing production information that is able to satisfy the various requirements of the manufacturing industry, such as a rapid product development and collaboration. Today, manufacturing companies are introducing a variety of data management systems, such as product data management and manufacturing process management. Business process reengineering is an essential process in the construction of these systems. It analyzes existing task procedures and work environments through “as-is” process analysis and defines “to-be” processes. However, existing task analysis methodologies, such as unified modeling language, architecture of integrated information systems, and computer-integrated manufacturing open system architecture, cannot address the required characteristics of product life cycle management as the purpose of those methodologies is to analyze and model specific attributes such as workflow and information. The aim of this research is to develop a methodology that can be applied in the business process reengineering phase for the effective construction of a product life cycle management system. We analyzed the objectives and characteristics of product life cycle management based on the existing product life cycle management definition analysis. Through this, we analyzed the strengths and weaknesses of the existing process modeling methodology. Finally, we developed the product life cycle information and process analysis methodology to integrate the analysis and design of task procedures, information, and work environments.

Confidence estimation of feedback information for logicdiagnosis

This paper proposes an estimation method for the confidence level of feedback information (CLFI), namely the confidence level of reported information in computer integrated manufacturing (CIM) architecture for logic diagnosis. This confidence estimation provides a diagnosis module with precise reported information to quickly identify the origin of equipment failure. We studied the factors affecting CLFI, such as measurement system reliability, production context, position of sensors in the acquisition chains, type of products, reference metrology, preventive maintenance and corrective maintenance based on historical data and feedback information generated by production equipments. We introduced the new ‘CLFI’ concept based on the Dynamic Bayesian Network approach and Tree Augmented Naïve Bayes model. Our contribution includes an on-line confidence computation module for production equipment data, and an algorithm to compute CLFI. We suggest it to be applied to the semiconductor manufacturing industry.

PENGARUH TEKNOLOGI DAN TUNTUTAN KONSUMEN TERHADAP PROFESI AKUNTANSI SAAT INI

PENGARUH TEKNOLOGI DAN TUNTUTAN KONSUMEN TERHADAP PROFESI AKUNTANSI SAAT INIThe objective of this article is to describe how technology and customer need influence accounting profession. Advanced technology has been changing almost all of human life. Innovations of computer equipment and program, as well as manufacturing tools influence accounting profession. This can be shown by generating various kinds of accounting computer application program and application of Material Requirement Planning (MRP), Computer Integrated Manufacturing (CIM), and Statistical Process Control (SPC). Customer’s need of accounting profession also has been changing paradigm that is as long as adhered. Conventional accounting is connoted by bookkeeping and auditing, while recently it is forced to develop its knowledge content and extent service spectrum e.g. management consultancy, strategic planning, and service consultancy of ISO 9000 and 14000. Keywords: accounting, influence, profession, technology

Absorptive capacity and the propensity to adopt advanced technology: the case of computer integrated manufacturing (CIM) systems

This paper examines the role of absorptive capacity (AC) on firms' intentions to adopt computer integrated manufacturing (CIM) systems, a particularly complex class of advanced manufacturing technology (AMT). I develop a simple model in which AC is reflected in the stocks of prior related knowledge the firm has accumulated in the past, arguing that these stocks constitute a sine qua non-condition for overcoming the inevitable knowledge barriers posed by advanced technologies to the adopting organisation. Moreover, I put forward the assertion that AC will moderate the influence posed by external environment on adoption decisions. Based on data collected from a sample of 87 Greek manufacturing SMEs, the results confirm these hypotheses: firms with high stocks of pre-existing AMT knowledge are more likely to adopt CIM systems, and they are also more likely to respond positively in environmental stimuli.

An AHP-based approach for the selection of HFMS: an Indian perspective

To meet the challenges imposed by today’s dynamic market conditions, it is the right time for the manufacturing companies to transit from traditional manufacturing system to advance manufacturing system such as computer numerical control (CNC), flexible manufacturing system (FMS) and computer integrated manufacturing (CIM) systems. CNC, FMS and CIM are very well-known terms in the manufacturing world. Developed countries have adopted and used all these manufacturing systems in their industries. Developing countries like India have used CNC technology in their plants but are reluctant to opt for the next phase of advance manufacturing system, i.e. FMS or CIM due to their high cost and heavy risk associated with them. Hence, a new manufacturing system, i.e. humanised FMS suitable to Indian industrial and social environment has been proposed in this paper. Analytic hierarchy process methodology has been utilised for the justification of this new manufacturing concept.

A methodology for integrating CAD and automatic inspection of standard manufactured features

Computer Integrated Manufacturing (CIM) can be defined as the development of a fully automatic manufacturing system from which a complete product can be manufactured in the most efficient way. The proposed methodology focuses on an integrated system of Computer Aided Design (CAD) and Computer Aided Inspection (CAI). The integration of CAD and Computer Aided Inspection Planning (CAIP) is essential for modern industries. The proposed framework of the integrated system is composed of three main modules: Automatic Features Extraction Module, Automatic Inspection Planning Module and Coordinate Measuring Machine Module. The purposes of this paper are (a) to address the issue of integration of CAD and inspection planning in which the prismatic features of design with inspection are linked efficiently and (b) to generate and execute inspection plans through the incorporation of CAIP with CMM using DMIS code programming. Finally, a case study is presented to demonstrate and validate the integrated system.

Optimisation of Resource Scheduling in VCIM Systems Using Genetic Algorithm

The concept of Virtual Computer-Integrated Manufacturing (VCIM) has been proposed for one and a half decade with purpose of overcoming the limitation of traditional Computer-Integrated Manufacturing (CIM) as it only works within an enterprise. VCIM system is a promising solution for enterprises to survive in the globally competitive market because it can exploit effectively locally as well as globally distributed resources. In this paper, a Genetic Algorithm (GA) based approach for optimising resource scheduling in the VCIM system is proposed. Firstly, based on the latest concept of VCIM system, a class of resource scheduling problems in the system is modelled by using agent-based approach. Secondly, GA with new strategies of handling constraint, chromosome encoding, crossover and mutation is developed to search for optimal solution for the problem. Finally, a case study is given to demonstrate the robustness of the proposed approach.

An effective hybrid graph and genetic algorithm approach to process planning optimization for prismatic parts

Computer-aided process planning is an important interface between computer-aided design and computer-aided manufacturing in computer-integrated manufacturing environments. In this paper, the complicated process planning is modeled as a combinatorial optimization problem with constraints, and a hybrid graph and genetic algorithm (GA) approach has been developed. The approach deals with process planning problems in a concurrent manner by simultaneously considering activities such as sequencing operations, selecting manufacturing resources, and determining setup plans to achieve the global optimal objective. Graph theory accompanied with matrix theory, as the basic mathematical tool for operation sequencing, is embedded into the main frame of GA. The precedence constraints between operations are formulated in an operation precedence graph (OPG). The initial population composed of all feasible solutions is generated by an elaborately designed topologic sort algorithm to the OPG. A modified crossover operator guaranteeing only feasible offspring generated is used, two types of mutation strategies are adopted, and a heuristic algorithm is applied to adjust the infeasible plan generated by the mutation operator to the feasible domain. A case study has been carried out to demonstrate the feasibility and efficiency of the proposed approach.

A multi-dimensional tabu search algorithm for the optimization of process planning

Computer-aided process planning (CAPP) is an essential component of computer integrated manufacturing (CIM) system. A good process plan can be obtained by optimizing two elements, namely, operation sequence and the machining parameters of machine, tool and tool access direction (TAD) for each operation. This paper proposes a novel optimization strategy for process planning that considers different dimensions of the problem in parallel. A multi-dimensional tabu search (MDTS) algorithm based on this strategy is developed to optimize the four dimensions of a process plan, namely, operation sequence (OperSeq), machine sequence (MacSeq), tool sequence (ToolSeq) and tool approach direction sequence (TADSeq), sequentially and iteratively. In order to improve its efficiency and stability, tabu search, which is incorporated into the proposed MDTS algorithm, is used to optimize each component of a process plan, and some neighbourhood strategies for different components are presented for this tabu search algorithm. The proposed MDTS algorithm is employed to test four parts with different numbers of operations taken from the literature and compared with the existing algorithms like genetic algorithm (GA), simulated annealing (SA), tabu search (TS) and particle swarm optimization (PSO). Experimental results show that the developed algorithm outperforms these algorithms in terms of solution quality and efficiency.

CIM Strategy And Strategic Management: An MIS Perspective

This study provides an overview of Computer-Integrated Manufacturing in a conceptual and managerial context, and analyzes the organizational structure and managerial approaches required for successful CIM. CIM is considered as the (vertical) integration of computerized manufacturing systems at the shop floor with Management Information Systems, and as the (horizontal) integration of functional areas from design, manufacturing to business functions. This implies an integrated, company-wide, MIS approach toward CIM rather than a traditional and functional attitude. In this context, the organizational structure that fits CIM technology will be analyzed.

An experimental design approach using TOPSIS method for the selection of computer-integrated manufacturing technologies

The selection of Computer-Integrated Manufacturing (CIM) technologies becomes more complex as the decision makers in the manufacturing organization have to assess a wide range of alternatives based on a set of attributes. Although, a lot of Multi-Attribute Decision-Making (MADM) methods are available to deal with selection applications, this paper aims to explore the applicability of an integrated TOPSIS and DoE method to solve different CIM selection problems in real-time industrial applications. Four CIM selection problems, which include selection of (a) an industrial robot, (b) a rapid prototyping process, (c) a CNC machine tool and (d) plant layout design, are considered in this paper. TOPSIS method and Design of Experiment (DoE) are used together to identify critical selection attributes and their interactions of all these cases by fitting a polynomial to the experimental data in a multiple linear regression analysis. This mathematical model development process involves TOPSIS experiments with the model. The regression meta-model greatly reduced the cost, time and amount of the calculation step in application the TOPSIS model. Application results were validated and shown that they provide good approximations to four decision making problem's results in the literature.

Evaluation of Telerobotic Interface Components for Teaching Robot Operation

Remote learning has been an increasingly growing field in the last two decades. The Internet development, as well as the increase in PC's capabilities and bandwidth capacity, has made remote learning through the internet a convenient learning preference, leading to a variety of new interfaces and methods. In this work, we consider a remote learning interface, developed in a Computer Integrated Manufacturing (CIM) Laboratory, and evaluate the contribution of different interface components to the overall performance and learning ability of end users. The evaluated components are the control method of the robotic arm and the use of a three-dimensional simulation tool before and during the execution of a robotic task. An experiment is designed and executed, comparing alternative interface designs for remote learning of robotic operation. A teleoperation task was given to 120 engineering students through five semesters. The number of steps required for completing the task, the number of errors during the execution, and the improvement rate during the execution were measured and analyzed. The results provide guidelines for a better design of an interface for remote learning of robotic operation. The main contribution of this paper is in the introduction of a new teaching tool for laboratories and the supplied guidelines for an efficient design of such tools.

CAE를 이용한 파인블랭킹 성형 해석

Computer-aided engineering (CAE) is the broad usage of computer software to aid in engineering tasks. It includes computer-aided design (CAD), computer-aided analysis (CAA), computer-integrated manufacturing (CIM), computer-aided manufacturing (CAM), material requirements planning (MRP), and computer-aided planning (CAP). In this study, the stress of mold analyzed using CAE technique. Punch loads were same difference between 0.5 % and 1.0 % of clearance, but punch load was decreased according to increasing of clearance. Punch load of pre-piercing process worked a little smaller than piercing process. Therefore, the hole of fine blanking process is also more efficient to manufacture the true size after pre-piercing.

Situation dependent decision selector for production control in testing and rework cell

This paper presents a production control approach for the testing and rework cell in a dynamic and stochastic computer integrated manufacturing (CIM) system. The proposed situation dependent decision selector (SDDS) observes the status of the system and jobs at every decision point, and makes its three different decisions on dispatching, pre-emption, and dispatching within pre-emption in real time. This paper also develops a new feature selection algorithm for the SDDS. Experimental results show that the SDDS is better than other static control rules and another dynamic control approach with respect to the number of tardy jobs.

Statistical Wear Model for Adhesively Bonded Tools

Computerized machinability data systems are essential for the selection of optimum conditions during process planning, and they form an important component in the implementation of computer integrated manufacturing (CIM) systems. Since statistical models for adhesively bonded tools are unavailable, the present paper presents a study of the development of a tool life, surface roughness and cutting force models for turning constructional steels, using adhesively bonded tools. These models are developed in terms of cutting speed, federate and depth of cut. These variables are investigated using design of experiments and utilization of response surface methodology (RMS).

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.

Evaluation of meta-heuristic approaches for scheduling optimisation of flexible manufacturing systems

Nowadays, in modern manufacturing, the trend is the development of Computer Integrated Manufacturing (CIM). The productivity of CIM is highly depending on the scheduling of Flexible Manufacturing System (FMS). Shortening the makespan leads to decreasing machines idle time, which results in improvement in CIM productivity. This paper proposes a meta-heuristic approach called Ant Colony Optimisation (ACO) method for scheduling optimisation of FMSs by considering multiple objectives, i.e., minimising the idle time of the machine and minimising the total penalty cost for not meeting the due date concurrently. The results available for the various existing meta-heuristic methods (Jerald et al., 2005) are compared with results obtained by ACO method.

Drivers and Barriers for Implementing Advanced Manufacturing Technology in China's Furniture Industry: An Exploratory Study

Results of this exploratory study provide insights into the implementation of advanced manufacturing technology (AMT) in China's furniture industry by using a multiple-case study approach. Qualitative interviews were conducted with upper managers and specialists in production and human resource management from four Chinese furniture firms that are viewed as pioneers in implementing computer-integrated manufacturing (CIM) in China's furniture industry. The findings show that key drivers for implementing AMT in the Chinese furniture firms are problems in production process, the need to reduce dependence on employees' work skills, and difficulties in recruitment arising from increased labor costs and a shortage of skilled workers. In addition, findings of the study reveal that the barriers to AMT implementation in Chinese furniture firms are not only from the technology side but also due to nontechnological aspects. These results could help decision makers in conducting process innovation with regard to both technological and nontechnological aspects, as well as in taking their interactions into account. Moreover, our findings may also help forest products industries in other emerging countries that are moving toward introducing new working systems.

A Taguchi-Neural-Based In-Process Tool Breakage Monitoring System in End Milling Operations

The use of CNC machines is one of the successful factors in the computer integrated manufacturing (CIM). Even though the CNC machine can automatically perform the machining processes, some of the situations that may significantly influence the quality of product such as a cutting tool breakage. Therefore, to prevent the machine from damaging and ensure the quality of product, it is important to develop a system that can monitor the tool conditions. The purpose of this study is to develop a Taguchi-neural-based in-process tool breakage monitoring system in end milling operations that can monitor the tool conditions and immediately response a proper action. For an in-process tool breakage monitoring system, a neural network was applied to making decisions of monitoring. One of the disadvantages of neural network is the training processes. It is difficult to determine an optimal combination of training parameters of neural networks. Traditionally, the try-and-error method is time-consuming and without systematic base. Therefore, the optimization of training parameters for neural networks using Taguchi design was applied to training the neural network model and to enhance the accuracy of the tool breakage monitoring system.

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.