Virtual manufacturing cells: A taxonomy of past research and identification of future research issues

This paper reviews prior research in the area of virtual manufacturing cells. A virtual manufacturing cell (VMC) is a group of resources that is dedicated to the manufacturing of a part family, though this grouping is not reflected in the physical structure of the manufacturing system. Distinguishing such groups in the production control system offers the possibility of achieving the advantages of cellular manufacturing in non-cellular manufacturing systems. The advantages may include improved flow performance, higher efficiency, simplified production control, and better quality. The paper reviews the previous publications on virtual manufacturing cells, to determine the methods and scope of present research. This results in a comprehensive framework which identifies the underlying principles of VMCs and classifies the different VMC concepts. It is shown that virtual manufacturing cells can significantly improve the performance of manufacturing systems. Based on the comprehensive review, many future research issues and high-impact research areas are also identified.     

Effectiveness of flexible routing control

Flexibility in part process representation and in highly adaptive routing algorithms are two major sources for improvement in the control of flexible manufacturing systems (FMSs). This article reports the investigation of the impact of these two kinds of flexibilities on the performance of the system. We argue that, when feasible, the choices of operations and sequencing of the part process plans should be deferred until detailed knowledge about the real-time factory state is available. To test our ideas, a flexible routing control simulation system (FRCS) was constructed and a programming language for modeling FMS part process plans, control strategies, and environments of the FMS was designed and implemented. In addition, a scheme for implementing flexible process routing called data flow dispatching rule (DFDR) was derived. The simulation results indicate that flexible processing can reduce mean flow time while increasing system throughput and machine utilization. We observed that this form of flexibility makes automatic load balancing of the machines possible. On the other hand, it also makes the control and scheduling process more complicated and calls for new control algorithms.     

Modeling the control of a flexible manufacturing cell for automatic verification and control program generation

Shortened product life-cycles decrease the output rate of manufacturing systems. Offline verification of the control systems promises to increase the output. However, to make offline verification possible some major improvements of the current development process of manufacturing systems are needed. Information handling and development of control programs based on information reuse are two of the most important improvement areas. This paper presents the results of the modeling of a real manufacturing cell according to a previously presented method for offline verification and program generation based on information reuse.     

Optimization of bioreactor using metabolic control analysis approach

A new methodology based on a metabolic control analysis (MCA) approach is developed for the optimization of continuous cascade bioreactor system. A general framework for representation of a cascade bioreactor system consisting of a large number of reactors as a single network is proposed. The kinetic and transport processes occurring in the system are represented as a reaction network with appropriate stoichiometry. Such representation of the bioreactor systems makes it amenable to the direct application of the MCA approach. The process sensitivity information is extracted using MCA methodology in the form of flux and concentration control coefficients. The process sensitivity information is shown to be a useful guide for determining the choice of decision variables for the purpose of optimization. A generalized problem of optimization of the bioreactor is formulated in which the decision variables are the operating conditions and kinetic parameters. The gradient of the objective function to be maximized with respect to all decision variables is obtained in the form of response coefficients. This gradient information can be used in any gradient-based optimization algorithm. The efficiency of the proposed technique is demonstrated with two examples taken from literature: biotransformation of crotonobetaine and alcohol fermentation in cascade bioreactor system.     

A model management systems approach to manufacturing systems design

Manufacturing systems design involves the solution of a complex series of interrelated problems. This complexity will increase in the future as manufacturing practices change to meet increased global competition. Research within manufacturing systems design has mainly been focused on finding improved models for solving particular problems, or extending existing modeling techniques. This has resulted in numerous modeling tools being available to support manufacturing systems design. However, little research work has been carried out into consolidating the existing theories and models. As a result, a large body of this work has not been applied in industry. Model management has evolved as a research area which investigates methods for storing, modifying, and manipulating models. This article describes a prototype model management system for manufacturing systems design. The objective here is not to develop “another” decision support system for manufacturing design, but to illustrate, through the development of a prototype system, a number of key ideas of how concepts from the area of model management systems can be used to support manufacturing systems design. The prototype model management system utilizes the structured modeling framework and uses an extended version of the structured modeling language. An important aspect of the prototype model management system is the incorporation of the model development task, thus allowing the system to be easily updated and adapted. The prototype system was evaluated using a range of queueing network models for manufacturing systems design.     

Enhanced Understanding of Pharmaceutical Materials Through Advanced Characterisation and Analysis

The impact of pharmaceutical materials properties on drug product quality and manufacturability is well recognised by the industry. An ongoing effort across industry and academia, the Manufacturing Classification System consortium, aims to gather the existing body of knowledge in a common framework to provide guidance on selection of appropriate manufacturing technologies for a given drug and/or guide optimization of the physical properties of the drug to facilitate manufacturing requirements for a given processing route. Simultaneously, material scientists endeavour to develop characterisation methods such as size, shape, surface area, density, flow and compactibility that enable a stronger understanding of materials powder properties. These properties are routinely tested drug product development and advances in instrumentation and computing power have enabled novel characterisation methods which generate larger, more complex data sets leading to a better understanding of the materials. These methods have specific requirements in terms of data management and analysis. An appropriate data management strategy eliminates time-consuming data collation steps and enables access to data collected for multiple methods and materials simultaneously. Methods ideally suited to extract information from large, complex data sets such as multivariate projection methods allow simpler representation of the variability contained within the data and easier interpretation of the key information it contains. In this review, an overview of the current knowledge and challenges introduced by modern pharmaceutical material characterisation methods is provided. Two case studies illustrate how the incorporation of multivariate analysis into the material sciences workflow facilitates a better understanding of materials.     

A Cascading Auction Protocol as a Framework for Integrating Process Planning and Heterarchical Shop Floor Control

A new contract net-style auction protocol is proposed as a framework for integrating process planning and shop floor control in heterarchical manufacturing systems. Process planning is partitioned into on-line and off-line activities; off-line process planning decisions are represented in a graph format and used as input for on-line process planning activities performed by machine controllers. Triggered by the opening round of an auction, the final on-line stages of process planning are dovetailed with the resource allocation process in the shop floor control system. The auction process allows final process planning decisions to be based on timely information, relying on the distribution of static process planning information rather than the distribution of a model of dynamic shop floor status and allowing a controller to identify all the primary and secondary resources and operations that must be provided for the incremental processing of a part.     

Simulation and analysis for sustainable product development

Purpose

Simulation plays a critical role in the design of products, materials, and manufacturing processes. However, there are gaps in the simulation tools used by industry to provide reliable results from which effective decisions can be made about environmental impacts at different stages of product life cycle. A holistic and systems approach to predicting impacts via sustainable manufacturing planning and simulation (SMPS) is presented in an effort to incorporate sustainability aspects across a product life cycle.

Methods

Increasingly, simulation is replacing physical tests to ensure product reliability and quality, thereby facilitating steady reductions in design and manufacturing cycles. For SMPS, we propose to extend an earlier framework developed in the Systems Integration for Manufacturing Applications (SIMA) program at the National Institute of Standards and Technology. SMPS framework has four phases, viz. design product, engineer manufacturing, engineer production system, and produce products. Each phase has its inputs, outputs, phase level activities, and sustainability-related data, metrics and tools.

Results and discussion

An automotive manufacturing scenario that highlights the potential of utilizing SMPS framework to facilitate decision making across different phases of product life cycle is presented. Various research opportunities are discussed for the SMPS framework and corresponding information models.

Conclusions

The SMPS framework built on the SIMA model has potential in aiding sustainable product development.     

Improved responsiveness of reconfigurable manufacturing systems using a standards-based approach to assess manufacturing capacity

Market acceptance of the S95 enterprise-control system integration standard and its adoption in IEC 62264, combined with the use of the ISO 15745 application integration scheme, offers a common framework for integrating diagnostic and control activities with asset maintenance and management activities. This paper describes a standard-based approach to improve the responsiveness of reconfigurable systems by using condition-based maintenance and diagnostics information to assess manufacturing capacity. Use of integration models and interoperability schemas enable manufacturing management to have greater visibility into the current state and the capabilities of manufacturing assets to meet scheduled manufacturing requirements.     

Defects tracking matrix for mass customization production based on house of quality

The vision of mass customization has driven a movement toward low volume, high variety mass customization production (MCP) at low price. However, defect identification and defect tracking in such systems are extremely difficult because of the frequent reconfiguration needed by the number of different part types and the interruption of the information flow about quality with each reconfiguration of the system. It is important to quickly rebuild quality information flow with MCP system’s reconfiguration synchronously. This paper introduces a defect tracking method based on Quality Function Deployment for every MCP system module. A defects tracking matrix (DTM) based on the House of Quality directly connects manufacturing technologies with quality defects inside a MCP module. Each MCP reconfiguration requires the DTMs’ rearrangement and DTM-chain is proposed. A dynamic reconstructing algorithm synchronizes the DTM-chain with each MCP reconfiguration. A case study demonstrates the usefulness of the DTM and DTM-chain.     

Darwin at High Temperature: Advancing Solar Cell Material Design Using Defect Kinetics Simulations and Evolutionary Optimization

Material defects govern the performance of a wide range of energy conversion and storage devices, including photovoltaics, thermoelectrics, and batteries. The success of large‐scale, cost‐effective manufacturing hinges upon rigorous material optimization to mitigate deleterious defects. Material processing simulations have the potential to accelerate novel energy technology development by modeling defect‐evolution thermodynamics and kinetics during processing of raw materials into devices. Here, a predictive process optimization framework is presented for rapid material and process development. A solar cell simulation tool that models defect kinetics during processing is coupled with a genetic algorithm to optimize processing conditions in silico. Experimental samples processed according to conditions suggested by the optimization show significant improvements in material performance, indicated by minority carrier lifetime gains, and confirm the simulated directions for process improvement. This material optimization framework demonstrates the potential for process simulation to leverage fundamental defect characterization and high‐throughput computing to accelerate the pace of learning in materials processing for energy applications.     

Marine systems analysis and modeling

Oceanography and marine ecology have a considerable history in the use of computers for modeling both physical and ecological processes. With increasing stress on the marine environment due to human activities such as fisheries and numerous forms of pollution, the analysis of marine problems must increasingly and jointly consider physical, ecological and socio-economic aspects in a broader systems framework that transcends more traditional disciplinary boundaries. This often introduces difficult-to-quantify, “soft” elements, such as values and perceptions, into formal analysis. Thus, the problem domain combines a solid foundation in the physical sciences, with strong elements of ecological, socio-economic and political considerations. At the same time, the domain is also characterized by both a very large volume of some data, and an extremely datapoor situation for other variables, as well as a very high degree of uncertainty, partly due to the temporal and spatial heterogeneity of the marine environment. Consequently, marine systems analysis and management require tools that can integrate these diverse aspects into efficient information systems that can support research as well as planning and also policy- and decisionmaking processes. Supporting scientific research, as well as decision-making processes and the diverse groups and actors involved, requires better access and direct understanding of the information basis as well as easy-to-use, but powerful tools for analysis. Advanced information technology provides the tools to design and implement smart software where, in a broad sense, the emphasis is on the man-machine interface. Symbolic and analogous, graphical interaction, visual representation of problems, integrated data sources, and built-in domain knowledge can effectively support users of complex and complicated software systems. Integration, interaction, visualization and intelligence are key concepts that are discussed in detail, using an operational software example of a coastal water quality model. The model comprises components of a geographical information and mapping system, data bases, dynamic simulation models, and an integrated expert system. An interactive graphical user interface, dynamic visualization of model results, and a hyper-text-based help-and-explain system illustrate some of the features of new and powerful software tools for marine systems analysis and modeling.     

De-risking Pharmaceutical Tablet Manufacture Through Process Understanding,Latent Variable Modeling,and Optimization Technologies

In pharmaceutical tablet manufacturing processes, a major source of disturbance affecting drug product quality is the (lot-to-lot) variability of the incoming raw materials. A novel modeling and process optimization strategy that compensates for raw material variability is presented. The approach involves building partial least squares models that combine raw material attributes and tablet process parameters and relate these to final tablet attributes. The resulting models are used in an optimization framework to then find optimal process parameters which can satisfy all the desired requirements for the final tablet attributes, subject to the incoming raw material lots. In order to de-risk the potential (lot-to-lot) variability of raw materials on the drug product quality, the effect of raw material lot variability on the final tablet attributes was investigated using a raw material database containing a large number of lots. In this way, the raw material variability, optimal process parameter space and tablet attributes are correlated with each other and offer the opportunity of simulating a variety of changes in silico without actually performing experiments. The connectivity obtained between the three sources of variability (materials, parameters, attributes) can be considered a design space consistent with Quality by Design principles, which is defined by the ICH-Q8 guidance (USDA 2006). The effectiveness of the methodologies is illustrated through a common industrial tablet manufacturing case study.     

Trade-off Modeling for Product and Manufacturing Process Design for the Environment

This article presents a method for integrating pollution prevention and concurrent engineering (simultaneous design of products and the manufacturing processes used to produce them). The central issue is unavoidable trade-offs, such as those among pollution, manufacturing cost, and quality. The probabilistic nature of the manufacturing process is exploited as an opportunity for pollution preventi0n.A decision tool in the form of a mathematical model is presented, which can be used by engineers and others with whom these trade-offs must be negotiated, Specifically, the method integrates statistical manufacturing process control into a mubobjective design optimization formulation. First, the framework of a multiattribute utilty function is developed to determine which objectives are both relevant and negotiable. Then, a statistical manufacturing process control experiment is conducted to formulate some of the constraints that prevent all objectives from being maximized. Simultaneously, information obtained from the experiment is also used to fine-tune the upper and lower bounds in the utility functions. The results of an industrial case study of a floor tile manufacturer are presented, from the manufacturer's viewpoint. The material choice and manufacturing process settings that result in the best combination of the conflicting objectives of product quality (measured in terms of scrap rate), air pollution, and manufacturing cost are determined. The analysis also reveals the irony that for this manufacturer; efforts to reduce solid waste through greater use of scrap materials increase air pollution levels     

Evaluation of Tools for Modeling Manufacturing Systems Design with Multiple Levels of Detail

This paper presents an investigation of simulation packages regarding their ability to model business processes related to manufacturing systems. Three simulation packages are investigated: VS7, SIMAN/CINEMA IV, and SIMFACTORY II.5. These packages are evaluated with regard to their capabily of modeling problems related to the manufacturing systems design (MSD) framework, which involves different levels of detail: the conceptual modeling level and the detailed design level. The investigation is based on a case study related to manufacturing systems. The main objective of this investigation is to examine the manufacturing simulation packages and their ability to offer variable detail modeling. Research findings suggest that no simulation environment offers sufficiently flexible facilities for the variable detailed modeling of manufacturing systems design. The paper proposes a method for systems entity classification to increase the levels of detail in an effective manner without duplication of data collection and model building efforts.     

On the Dependability Design of Manufacturing Information Systems

In computer integrated manufacturing environments, dependability is a crucial attribute for the production management and control information system, which should be carefully assessed during system design. This paper discusses a global approach for assessment of the dependability of industrial information systems, covering all the phases of a study, from initial system modeling to dependability analysis and evaluation. After the presentation of the modeling concepts and tools, the paper focuses on the dependability evaluation. Two complementary algorithms are discussed, one based on the device stage method and the other on the automatic derivation of analytical expressions for the state probabilities and their symbolic evaluation. The central feature of these algorithms is their ability to deal with nonexponential stochastic processes, a fundamental requirement for this class of systems.     

A tool for modeling strategic decisions in cell culture manufacturing

The development of a prototype tool for modeling manufacturing in a biopharmaceutical plant is discussed. A hierarchical approach to modeling a manufacturing process has been adopted to confer maximum user flexibility. The use of this framework for assessing the impact of manufacturing decisions on strategic technical and business indicators is demonstrated via a case study. In the case study, which takes the example of a mammalian cell culture process delivering a therapeutic for clinical trials, the dynamic modeling tool indicates how manufacturing options affect the demands on resources and the associated manufacturing costs. The example illustrates how the decision-support software can be used by biopharmaceutical companies to investigate the effects of working toward different strategic goals on the cost-effectiveness of the process, prior to committing to a particular option.     

Manufacturing Cost Modeling for Product Design

The process of product design is driven toward achieving design specifications while meeting cost targets. Designers typically have models and tools to aid in functional and performance analysis of the design but few tools and little quantitative information to aid in cost analysis. Estimates of the cost of manufacture often are made through a cost multiplier based on material cost. Manufacturing supplies guidelines to aid in design, but these guidelines often lack the detail needed to make sound design decisions. A need was identified for a quantitative way for modeling manufacturing costs at Motorola. After benchmarking cost modeling efforts around the company, an activity-based costing method was developed to model manufacturing cycle time and cost. Models for 12 key manufacturing steps were developed. The factory operating costs are broken down by time, and cost is allocated to each product according to the processing it requires. The process models were combined into a system-level model, capturing subtle yet realistic operational detail. The framework was implemented in a software program to aid designers in calculating manufacturing costs from limited design information. Since the information tool provides an estimate of manufacturing costs at the design prototype stage, the development engineer can identify and eliminate expensive components and reduce the need for costly manufacturing processing. Using this methodology to make quantitative trade-offs between material and manufacturing costs, significant savings in overall product costs are achieved.     

Performance management of manufacturing system networks

Performance management of communication networks is critical for speed, reliability, and flexibility of information exchange between different components, subsystems, and sectors (e.g., factory, engineering design, and administration) of production process organizations in the environment of computer integrated manufacturing (CIM). Essential to this distributed total manufacturing system is the integrated communications network over which the information leading to process interactions and plant management and control is exchanged. Such a network must be capable of handling heterogeneous traffic resulting from intermachine communications at the factory floor, CAD drawings, design specifications, and administrative information. The objective is to improve the efficiency in handling various types of messages, e.g., control signals, sensor data, and production orders, by on-line adjustment of the parameters of the network protocol. This paper presents a conceptual design, development, and implementation of a network performance management scheme for CIM applications including flexible manufacturing. The performance management algorithm is formulated using the concepts of: (1) Perturbation analysis of discrete event dynamic systems; (2) stochastic approximation; and (3) learning automata. The proposed concept for performance management can also serve as a general framework to assist design, operation, and management of flexible manufacturing systems. The performance management procedure has been tested via emulation on a network test bed that is based on the manufacturing automation protocol (MAP) which has been widely used for CIM networking. The conceptual design presented in this paper offers a step forward to bridging the gap between management standards and users' demands for efficient network operations since most standards such as ISO and IEEE address only the architecture, services, and interfaces for network management.     

The Structure of Manufacturing Systems: Insights on the Impact of Variability

A classic issue in manufacturing strategy is positioning, that is, the appropriate structure for the manufacturing system. At its simplest, the choice is between a job shop and a flow line; but if the system has to produce a variety of different products,then it also is necessary to decide on focus, the degree of specialization. While effective use of resources is essential, it also is necessary to consider the ability of the system to cope with variability and disturbances. Using a variety of queueing models of manufacturing systems, it is possibleto get some useful insights into positioning and focus.