A Part Scheme in Single-Stage Multimachine Systems

In current manufacturing environments, manufacturing orders are often characterised by unstable market demand, short product life cycles, carieties of products, and shory production lead times. In order to fulfil such manufacturing orders, a recent trend in flexible manufacturing systems (FMS) is to use versatile machines with fast tool delivery devices. In contrast to a conventional FMS that mainly focuses on part flows, tool flow control is important in single-stage multimachine systems (SSMS), which consist of versatile machines and fast tool delivery devices. This study proposes a part release scheme for SSMS, which considers the projected tool competition at the part release stage. This scheme can be applied to a real environment to improve system performance. The effectiveness of the scheme is demonstrated through a series of simulation experiments. Interpretations of the results are also presented.     

Object-oriented methods for manufacturing information systems

Object-oriented programming (OOP) is now widely used in application software development. OOP has advantages connected with handling complexity, reusability, extendability, modularity and data abstraction, enabling it to handle modern programming requirements more effectively than conventional programming methods. Successful advanced manufacturing systems demand increasing complexity, flexibility and integration between computer applications. An object-oriented approach is particularly promising for the design and development of manufacturing information systems. This paper outlines the concepts of object-oriented methods, and describes an object-oriented application development methodology for manufacturing information systems. A CASE (Computer-Aided Software Engineering) tool is used for system modelling and for direct source-code generation. A case study describing the development of a quality management information system is presented, which was implemented using a C++ development environment. Although the research described here is concerned with quality management information systems, the proposed design methodology is applicable to other areas of manufacturing, and conclusions are drawn concerning the uses of OOP in manufacturing information systems generally.     

A methodology to define a reconfigurable system architecture for a compact heat exchanger assembly machine

Due to the unexpected, fast, and constant changes of market requirements and the hypercompetency, robust manufacturing systems are needed that adjust easily to operational variability and the customized product supply. The simply substitution of components, software, hardware, and/or their adaptation by parameters resetting are an attractive option to face this challenge. Short product life cycles are an undeniable consequence and evidence of this. For this reason, to develop products or services profitably in the product manufacturing field, it is common to use the product family concept, which involves sharing components, functional features, and manufacturing process, both to make a cheaper product development process and to obtain customized products. A new generation of manufacturing systems that deploy characteristics such as adaptability and flexibility responding to the market dynamics called reconfigurable manufacturing systems (RMS) are required by market according to manufacturing experts. The manufacturing systems with modular architecture are the best way to meet flexible and adaptable RMSs because they allow reconfiguration by a simple module substitution or by resetting module operation parameters. This paper presents a design methodology developed to obtain modular RMS. The method integrates the utilization of modular architecture principles, selection algorithms (analytical hierarchical process), clustering algorithms (average linkage clustering algorithm), family product features and functional system analysis in the classical product design process. The methodology proposed allows defining the most adequate modular system architecture and the modular definition of the reconfiguration variables that are needed to reach the flexibility required. A real study case about a heat exchanger assembly machine is presented where this methodology is applied in order to present an evidence of its usefulness.     

Modelling and analysis of multiple cluster tools system with random failures using coloured Petri net

Semiconductor manufacturing is among the most complicated and expensive operation systems encountered today and multiple cluster tool system has become an important technology in semiconductor manufacturing systems with the advantages of higher yields and shorter cycle times. Modelling and simulation has become a standard methodology in order to understand and predict performance of semiconductor manufacturing systems. Resources random failures during process execution are one major concern regarding system performance measured in terms of throughput and cycle time. This study aims to models and analyse random failures of processing modules of multiple cluster tool systems using coloured Petri net method. The impact of different input factors on system throughput and cycle time is presented.     

A material selection methodology and expert system for sustainable product design

Material selection is one of the main phases of product design process that has great impact on the manufacturing of sustainable products. One of the best approaches of material selection for sustainable products is life cycle engineering (LCE). But LCE is a costly and cumbersome task and it is not economic to perform this task for a large number of proposed materials in order to choose the most suitable one for a sustainable product. Instead, it is more reasonable to make a preliminary filtering on the proposed materials and obtain a shorter list of candidate materials and then perform LCE on alternatives which are obtained from preliminary filtering. Since environmental friendliness of materials is a critical sustainability issue, so it is a good criterion for preliminary filtering of alternatives. In this paper, a new methodology is proposed to support preliminary filtering of alternatives from environmental viewpoint. The methodology uses the knowledge of experts in the field of eco-design. The knowledge is translated to decision making rules and a decision tree is developed to guide the choice. In order to use the capabilities of frame-based systems, an object-oriented approach for representation of knowledge is also proposed. Moreover, a prototype hybrid expert system based on the proposed methodology called material selection expert system for sustainable product design is developed to support the task of preliminary filtering. Finally, a case study from tire manufacturing industries is presented to show the validity of the proposed system. The results show that the system can determine the appropriate candidate materials and hence improve the possibility of manufacturing of more sustainable products. Eliminating alternatives that do not have the necessary conditions for sustainable product leads to a large saving in time and cost of the LCE evaluation process     

An integrated object-oriented approach for design and analysis of an agile manufacturing control system

The agile manufacturing paradigm has emerged as an important concept in the development of manufacturing systems. The control software, developed based on the object-oriented technology, leads to reusability, reconfigurability, and scalability; and the agility of a manufacturing control system can be achieved. In this research, an efficient and systematic methodology for developing an object-oriented agile manufacturing control system is proposed. The proposed development process is divided into four stages: functional analysis, static structural analysis, behavior analysis and verification, and system implementation. The Integration Definition for Function Modeling (IDEF0), Object-Oriented Petri Net (OPN), and Unified Modeling Language (UML) are integrated into the corresponding stages based on their characteristics. In order to develop the system rapidly and efficiently, the transformation rules between the IDEF0 and OPN, and between the OPN and sequence diagram are conducted. In addition, the attributes and operations for each object are also defined directly from the OPN model. The result of the integrated IDEF0/OPN/UML systematically leads to object-oriented control software design for manufacturing systems. Finally, an assembly and packaging system is given to illustrate how the integrated object-oriented approach is implemented for developing the manufacturing control system.     

Remote control of a robot in a map network

The automated control of manufacturing devices on a common communications network is a necessity for the factory of the future. The manufacturing automation protocol (MAP) represents a major effort by a group of companies towards meeting this need, and apparently is becoming a standard for factory-floor communications. In this project, an ASEA 2000 robot was used with a computer-controlled ply-cutting machine in a simulated factory sheet-metal cell to demonstrate coordinated inter- and intra-cell communications. Both machines used a MAP network to send and receive information from the cell-controller computer, and to coordinate cell operation. The methodology, hardware and software required to adapt the ASEA robot to the MAP network are described. This methodology will be useful in adapting other computer-controlled manufacturing devices to MAP networks.     

Informational model of digital manufacturing (ISA-95 standard)

The development of an information model of digital manufacturing is considered. The goal of the model is maximum integration of the management systems for enterprise resources (ERP) and the product life cycle (PLM) and for operational management (MES), by expanded application of the provisions of the ISA-95 standard. A methodology is proposed for creating digital doubles of real production processes by the development of the Herbarium integrated engineering software platform (Foundation for Advanced Studies).     

Automatic transformation of logic models within engineering of embedded mechatronical units

Engineering of manufacturing systems is one of the most important aspects within the life cycle of manufacturing systems in terms of cost. Within the engineering process, several engineering activities are executed by different experts commonly using specific tools for the design of the different parts of the system. To reduce engineering costs beneath, two main approaches arise. The first is based on the use of libraries of mechatronical units as reusable artifacts. In this case, manufacturing systems are represented as a hierarchy of mechatronic units. The second option is to achieve the seamless connection of the different engineering tools exploiting a common data exchange format. This latter approach allows avoiding both double engineering and faults within the engineering process. Within this paper, a novel approach combining both options is proposed, and its effects are analyzed through an example. It considers the application of mechatronical units within the engineering process of manufacturing systems as well as a common data exchange format for the logic information required for designing the control system within the engineering of manufacturing systems. The latter provides a data exchange format for the overall engineering process, including not only model information exchange but also its embedding. This paper discusses the benefits of the data exchange format for logic models in detail.     

An optimization-based control strategy for energy efficiency of discrete manufacturing systems

In order to reduce the global energy consumption and avoid highest power peaks during operation of manufacturing systems, an optimization-based controller for selective switching on/off of peripheral devices in a test bench that emulates the energy consumption of a periodic system is proposed. First, energy consumption models for the test-bench devices are obtained based on data and subspace identification methods. Next, a control strategy is designed based on both optimization and receding horizon approach, considering the energy consumption models, operating constraints, and the real processes performed by peripheral devices. Thus, a control policy based on dynamical models of peripheral devices is proposed to reduce the energy consumption of the manufacturing systems without sacrificing the productivity. Afterward, the proposed strategy is validated in the test bench and comparing to a typical rule-based control scheme commonly used for these manufacturing systems. Based on the obtained results, reductions near 7% could be achieved allowing improvements in energy efficiency via minimization of the energy costs related to nominal power purchased.     

Assessing the structural complexity of manufacturing systems configurations

Modern manufacturing systems are increasingly required to be flexible and adaptable to changing market demands, which adds to their structural and operational complexity. One of the major challenges at the early design stages is to select a manufacturing system configuration that both satisfies the production functional requirements and is easy to operate and manage. A new metric for assessing the structural complexity of manufacturing system configurations is presented in this paper. The proposed complexity metric incorporates the quantity of information using an entropy approach. It accounts for the complexity inherent in the various modules in the manufacturing system through the use of an index derived from a newly developed manufacturing systems classification code. The code captures the effect of various component types and technologies used in a manufacturing system on the system’s structural complexity. The presented metric would be helpful in selecting the least complex manufacturing system configuration that meets the requirements. An engine cylinder head production system is used to illustrate the application of the proposed methodology in comparing feasible but different manufacturing system configurations capable of producing the cylinder head based on their structurally inherent complexity.     

New criterion for evaluating the aptitude of measurement systems in process capability determination

In practice, carrying out statistical process control of manufacturing processes requires the use of measurement systems. These systems are not totally reliable because they are subject to inherent variability. This paper investigates the influence of measurement uncertainty on the analysis of manufacturing process capability. A new methodology is described that helps overcome the effect of measurement uncertainty in order to obtain a more accurate assessment of the capability of the production processes. This methodology presents a solution that ensures the metrological confirmation of the measurement processes, and it was developed for manufacturing processes centred at a nominal value and for off-centred processes. Moreover, an improved capability index integrated into the statistical process control is proposed for evaluating measurement systems. The index helps identify manufacturing process quality risks associated with uncertainty in measurement systems.     

Prediction-based manufacturing center self-adaptive demand side energy optimization in cyber physical systems

Cyber physical systems（CPS） recently emerge as a new technology which can provide promising approaches to demand side management（DSM）, an important capability in industrial power systems. Meanwhile, the manufacturing center is a typical industrial power subsystem with dozens of high energy consumption devices which have complex physical dynamics. DSM, integrated with CPS, is an effective methodology for solving energy optimization problems in manufacturing center. This paper presents a prediction-based manufacturing center self-adaptive energy optimization method for demand side management in cyber physical systems. To gain prior knowledge of DSM operating results, a sparse Bayesian learning based componential forecasting method is introduced to predict 24-hour electric load levels for specific industrial areas in China. From this data, a pricing strategy is designed based on short-term load forecasting results. To minimize total energy costs while guaranteeing manufacturing center service quality, an adaptive demand side energy optimization algorithm is presented. The proposed scheme is tested in a machining center energy optimization experiment. An AMI sensing system is then used to measure the demand side energy consumption of the manufacturing center. Based on the data collected from the sensing system, the load prediction-based energy optimization scheme is implemented. By employing both the PSO and the CPSO method, the problem of DSM in the manufac~ring center is solved. The results of the experiment show the self-adaptive CPSO energy optimization method enhances optimization by 5% compared with the traditional PSO optimization method.     

制造企业应用系统实施顺序决策支持技术

通过构建企业信息化系统的状态矩阵,综合考虑各应用系统的收益和实施周期、应用系统之间的协同特性、企业资金和时间等要素基础上,建立了应用系统实施顺序决策支持模型。从企业特性和企业竞争重点的角度探讨了应用系统的收益评估方法,从应用系统之间数据流的角度阐述了协同系数矩阵的构建方法,从而可以求解模型, 为决策提供有效支持。最后运用上述方法对某企业信息化应用系统实施顺序决策进行了案例分析。     

Developing manufacturing control software: A survey and critique

The complexity and diversity of manufacturing software and the need to adapt this software to the frequent changes in the production requirements necessitate the use of a systematic approach to developing this software. The software life-cycle model (Royce, 1970) that consists of specifying the requirements of a software system, designing, implementing, testing, and evolving this software can be followed when developing large portions of manufacturing software. However, the presence of hardware devices in these systems and the high costs of acquiring and operating hardware devices further complicate the manufacturing software development process and require that the functionality of this software be extended to incorporate simulation and prototyping.This paper reviews recent methods for planning, scheduling, simulating, and monitoring the operation of manufacturing systems. A synopsis of the approaches to designing and implementing the real-time control software of these systems is presented. It is concluded that current methodologies support, in a very restricted sense, these planning, scheduling, and monitoring activities, and that enhanced performance can be achieved via an integrated approach.     

New friction welding process for pipeline girth welds—welding time optimisation

CAD/CAM systems are the important interface for automating manufacturing processes to accommodate the varying market demands. However, they are often operated in an isolated environment and are unable to communicate with each other. Rapid development and enhancement of the network technology had made it possible for manufacturing processes to be implemented in a distributed environment. The purpose of this study is to develop a dispersed networked multi-axis surface manufacturing system. The proposed research uses the Integrated Definition for Function Modelling (IDEF0) methodology to analyze the manufacturing activities and adopts the Common Object Request Broker Architecture (CORBA) standard as the infrastructure of software components. Using IDEF0, the manufacturing activities can be analyzed and represented as a hierarchical and structural functional model. The developed system has the “plug-and-play” capability and can be integrated with other development teams to achieve information sharing. On-line test of the prototype system has been implemented collaboratively by three development teams and the effectiveness of the developed system has also been confirmed. The developed system has successfully integrated resources of different locations through a network and can effectively reduce the product development and manufacturing time, thus enhancing the global competitiveness of the industry.     

Fusion of qualitative bond graph and genetic algorithms: a fault diagnosis application

In this paper, the problem of fault diagnosis via integration of genetic algorithms (GA's) and qualitative bond graphs (QBG's) is addressed. We suggest that GA's can be used to search for possible fault components among a system of qualitative equations. The QBG is adopted as the modeling scheme to generate a set of qualitative equations. The qualitative bond graph provides a unified approach for modeling engineering systems, in particular, mechatronic systems. In order to demonstrate the performance of the proposed algorithm, we have tested the proposed algorithm on an in-house designed and built floating disc experimental setup. Results from fault diagnosis in the floating disc system are presented and discussed. Additional measurements will be required to localize the fault when more than one fault candidate is inferred. Fault diagnosis is activated by a fault detection mechanism when a discrepancy between measured abnormal behavior and predicted system behavior is observed. The fault detection mechanism is not presented here.     

Heuristics for the design of part-orienting systems

In many manufacturing systems, parts must be fed to automatic machines in a specific orientation. This is often accomplished by what are known as part-orienting systems (POSs). A POS consists of one or more separate devices that orient parts, usually with multiple orientations. A theoretical analysis along with the development of some heuristic algorithms is carried out in order to treat the problem of efficient selection and ordering of part-orienting devices that make up a POS. It is indicated that the size of such problems can be quite large in the context of flexible manufacturing systems which may require what are known as flexible part-orienting systems for their efficient operation. Computational experiments are performed in order to evaluate the relative performance of the heuristic algorithms.