Strategic configuration of flexible electronics assembly facilities facing stochastic requirements

Flexible configuration of manufacturing facilities is a key strategy for efficiently improving market responsiveness and market share in the face of uncertain future product demand. Flexible facility configurations can produce an efficient production system that allows higher capacity utilization given uncertainty in product demand and mix. The aim of this paper is to consider the alternative choices of flexible equipment available at the strategic planning level and to make decisions about the facility design and configuration that best suits the specific needs of the manufacturing system under consideration. A chance constrained mixed integer programming model for strategic configuration and capacity planning of flexible multiple-stage production facilities under time-varying production requirements is introduced in this paper. It is an integrated model that determines the number of assembly lines required, the flexible automation levels required in each line, capacity levels, and product assignments/reassignments for a multiple-stage production system, considering the stochastic nature of the demand. A two-step heuristic based on genetic algorithms is proposed and tested. Experimental results indicate that the two-step heuristic performs well in terms of both computation speed and solution accuracy.     

On the trade-offs between risk pooling and logistics costs in a multi-plant network with commonality

This paper examines the benefits and costs of two alternative manufacturing network configurations in the presence of component commonality. We evaluate the trade-off between the decreased logistics costs and loss of risk-pooling benefits in plant networks which spread component manufacturing over each plant (product network) as compared to those that consolidate component manufacturing in a single plant (process network). We examine for conditions that mean that a product network would be chosen instead of a process network and vice-versa. We find that the risk-pooling benefit obtained by consolidating common subassembly production is reduced when the cost of acquiring common component capacity is sufficiently high or low. A post-optimality sensitivity analysis for the process network provides insights into subtle substitution effects, which are a direct outcome of cost mix differentials and network structure and complementarity effects, which are induced by the considered sequential assembly system. Our results suggest that the impact of operational cost parameters on strategic decisions can often be non-intuitive. Overall, our analysis provides a link between strategic and operational decision-making in supply chain management, in the context of multi-plant configuration.     

Sustainability priorities across the strategic and operational level in packaging development

Sustainability is well‐established in many companies' strategic postures. However, executing sustainability‐related goals often lags at the operational level. This study analyses how decision‐making processes in packaging development at different hierarchical levels are characterized in achieving a sustainability consensus. This research focuses on the alignment of the strategic and operational levels of packaging development in relation to the integration of sustainability considerations. This materializes in a stakeholder perspective on packaging development and an analysis of targets aiming for the integration of sustainability considerations in such development processes. The involvement and decision making by internal stakeholders, the involvement of external stakeholders and sustainability target setting are considered as conditions causing the outcome of interest: levels of sustainability implementation on both the strategic and the operational levels of packaging development. By using a set‐theoretic method, we address that different compositions of stakeholder involvement and target setting might cause the same level of sustainability priority at the strategic and operational levels. For data analysis, we use a fuzzy‐set qualitative comparative analysis (fsQCA) with empirical data derived from survey responses by packaging experts. This approach is motivated by its ability to address the complexity of the interplay of case characteristics within development processes. The research findings provide several indications of a limited alignment of a company's strategic sustainability ambition with the operational activities of multidisciplinary packaging development teams. The insights on the sustainability‐related configurations of stakeholders and target setting provide guidance for managing projects across the strategic and operational levels in improving sustainable packaging development.     

Capacity planning through queueing analysis and simulation-based statistical methods: a case study for semiconductor wafer fabs

This paper presents a comprehensive framework for the strategic capacity expansion of production equipment in semiconductor manufacturing, and the proposed approach is applied to a model of an actual wafer fabrication facility. It is the intention of this work to show that, once intelligently integrated, an analytical queueing model and a numeric computer simulation model can be used synergistically and can lead to a better alternative method than methods restricted to only one of them. The outcome of our methods is a number of good system configurations, each of which is characterised by its cycle time (CT)–throughput (TH) profile. Such profiles fully describe the system's comprehensive performance over a wide range of demand scenarios (involving varying product mix), and hence can be used to thoroughly evaluate alternative configurations in capacity expansion decisions.     

Strategic Thrust of Manufacturing Automation Decisions: A Conceptual Framework

American manufacturing firms increasingly consider automation as the means to increase productivity and improve their competitiveness. However, decisions to automate do not always produce the expected results and lead to further frustration. The so called “islands of automation” are often blamed for such failures and other technological alternatives such as computer integrated manufacturing (CIM) are adopted on a piece-meal fashion. This paper examines the adoption of new technology in general, and die decision to automate in particular, from a strategic perspective. In order to deal with the underlying complexities of automation, a conceptual framework is developed that can guide decision makers through a step-by-step process. Within an experimental analysis context, a decision support system is built that uses the “Expert Choice” cell to test the effectiveness of the introduced framework. The results indicate that the study's method can greatly enhance the decision making capabilities of firms contemplating automation     

Cooperation between drivers and automation: implications for safety

The purpose of this paper is to develop a recently proposed framework of human–machine cooperation (Hoc, J.M., 2001. Towards a cognitive approach to human–machine cooperation in dynamic situations. International Journal of Human–Computer Studies, 54, 509–540) and apply it to the domain of in-car automation. Previous models of automation (e.g. Sheridan, T.B. and Verplanck, W.L., 1978. Human and computer control of undersea teleoperators. Cambridge, MA: MIT Man–Machine Systems Laboratory) delineate the roles of human and machine in a task-based manner and primarily from the viewpoint of machine requirements. However, with increasing arguments that automation should support the human operator rather than replace them (e.g. Young, M.S., Stanton, N.A., and Harris, D., 2007. Driving automation: learning from aviation about design philosophies. International Journal of Vehicle Design, 45(3), 323–338), Hoc's (2001) framework offers a means of modelling the interaction from the perspective of teamwork–that is, from the viewpoint of human requirements. In the present context, the framework describes how both the driver and the automation can be considered as separate agents pursuing their own goals while trying to facilitate a common task, but who may interfere with each other positively (e.g. mutual control) or negatively (mutual conflict). Vehicle automation, as an area of fervent research in ergonomics at present, provides the opportunity to explore the framework and use it to interpret current and emerging research findings. It is suggested here that many of the psychological problems underlying the introduction of in-car automation are a result of suboptimal communications between human and machine, and the framework is used to propose directions for future research in this area.     

Developing an analytical framework for study of emerging country multinationals’ operations management

The rise of emerging country multinationals (EMNEs) is opening new perspectives for the study of international operations management (IOM). Research may address issues which are inexistent when the object of study is long-established developed country multinationals (DMNEs). One of the issues that may be noticed, and will be studied in this article, has to do with the design and implementation of new international operations networks. In contrast to DMNEs, internationalisation of EMNEs is strongly influenced by two further factors: country-of-origin effects and role in global production networks. Therefore, studies of EMNEs’ international operations networks must embrace two other analytical levels besides the network level: the strategic level of the headquarters and the operational level of the subsidiaries. The analytical framework in this study has been developed through the use of constructs and concepts from both IOM and international business literatures. Such framework applied to three Brazilian multinationals leads to relevant insights on the internationalisation of EMNEs as well as the design and implementation of international operations networks for such late-moving firms.     

Design of an FMS decision support system

Flexible manufacturing system (FMS) is an integrated system consisting of computer numerical control machine tools and automated material handling system controlled by an overall control computer system. The FMS design is broken down into strategic, tactical and operational level designs. This research is concerned with the development of a decision support system for the design of FMS (FMSDDS. Simulation is used as a primary analysis tool, making the DSS capable of solving problems at all three levels. The decision making ability is provided by a multi-attribute utility model which accounts for both quantitative and qualitative factors that affect a decision. The FMSDSS is implemented using three routines: input, analysis, and output. The input routine helps the user to select feasible FMS configurations interactively. The analysis routine consists of a generalized FMS simulation model. This routine analyses the FMS alternatives selected and provides the information required for the output analysis. The qualitative and quantitative measures of performance that have to be considered for decision making are handled by the output routine. It also combines performance measures of different units such as time and cost. The DSS is modular and hence future enhancements can be readily added.     

Combined strategic and operational planning – an MILP success story in chemical industry

We describe and solve a real world problem in chemical industry which combines operational planning with strategic aspects. In our simultaneous strategic & operational planning (SSDOP) approach we develop a model based on mixed-integer linear (MILP) optimization and apply it to a real-world problem; the approach seems to be applicable in many other situations provided that people in production planning, process development, strategic and financial planning departments cooperate. The problem is related to the supply chain management of a multi-site production network in which production units are subject to purchase, opening or shut-down decisions leading to an MILP model based on a time-indexed formulation. Besides the framework of the SSDOP approach and consistent net present value calculations, this model includes two additional special and original features: a detailed nonlinear price structure for the raw material purchase model, and a detailed discussion of transport times with respect to the time discretization scheme involving a probability concept. In a maximizing net profit scenario the client reports cost saving of several millions US$. The strategic feature present in the model is analyzed in a consistent framework based on the operational planning model, and vice versa. The demand driven operational planning part links consistently to and influences the strategic. Since the results (strategic desicions or designs) have consequences for many years, and depend on demand forecast, raw material availability, and expected costs or sales prices, resp., a careful sensitivity analysis is necessary showing how stable the decisions might be wit h respect to these input data.     

How operators make use of wide-choice adaptable automation: observations from a series of experimental studies

The present paper is concerned with the design of adaptable automation. It analyses the aggregated data from five experiments (N = 154) to examine which automation levels operators prefer, how often they switch between them, and whether performance is associated with frequent switching or the automation levels being used. Using wide-choice adaptable automation (i.e. up to six levels were offered), the experiments were conducted using a PC-based simulation of a complex work environment. The results showed that about 95% of operators had a clearly preferred automation level, which they used for more than 50% of the time. They strongly preferred intermediate automation levels over levels at the higher and lower ends of the scale. Most operators switched rarely between levels and when they did, they usually made small adjustment rather than large changes. Several implications for the design of adaptable automation were derived from the empirical data.     

A formal control-theoretic model of a human–automation interactive manufacturing system control

This paper describes a human–automation interactive manufacturing system and presents a formal model for describing and controlling the system. The model presented in this paper considers a system from two perspectives: structural and operational perspectives. Human and an automated controller are considered agents that cooperate to achieve given goals by executing assigned tasks. A human–automation interaction is described with a particular communication model between two agents that exchanges messages. A system control schema and human tasks are modelled separately and then integrated in a formal manner using a modified communicating finite state machine framework. An interface model that coordinates the message exchanges between two agents is then introduced. An automated shop floor control system with a human material handler is modelled with the proposed framework and a simple illustrative example is provided.     

Formulation to obtain the most reliable aggregate mix with quantity and other constraints

The aggregate batch mixing problem determines the proportion (or relative masses) in which aggregate batches with different gradations are to be blended so as to achieve a target mix with a given gradation. As shown in previous studies, the gradation of a batch is not homogeneous and should be considered stochastic. Also, when batches are blended in the field there are random variations in the masses or proportions of individual batches in the mix. Assuming batch gradation and blend masses as stochastic implies that the notion of a mix (blend) satisfying the gradation of a target mix becomes stochastic. In such a framework, every mix has a reliability with which it satisfies the definition of the target mix. In addition, a mix is also required to satisfy various restrictions. This article presents an optimization formulation to determine the most reliable mix while satisfying restrictions on available quantity, budget, etc.     

Strategic acquisition of new manufacturing technology: a review and research framework

A framework for evaluating acquisition of new manufacturing technology is presented based on extensive reviews of various approaches available in the literature. The suggested evaluation procedure involves three hierarchical levels, namely, strategic evaluation, operational evaluation and financial evaluation. The need for quantifying intangible and complex strategic benefits, and comparing them with tangible financial benefits at the same level is eliminated. The paper describes a methodology for strategic evaluation, and suggests techniques that can be used for operational and financial evaluation. The framework identifies important research areas and provides guidelines to develop a better procedure for evaluating acquisition of new manufacturing technology.     

Strategic,tactical and operational decisions in multi-national logistics networks: A review and discussion of modelling issues

The rapidly developing worldwide marketplace is leading to the geographical dispersion of production, assembly and distribution operations. This paper deals with three aspects of international logistics networks: strategic, tactical and operational. The strategic level designs the logistics network, including prescribing facility locations, production technologies and plant capacities. The tactical level prescribes material flow management policies, including production levels at all plants, assembly policy, inventory levels, and lot sizes. The operational level schedules operations to assure in-time delivery of final products to customers. This paper reviews the literature that deals with strategic, tactical and operational levels and discusses relevant modelling issues.     

A discrete-time Bayesian network reliability modeling and analysis framework

Dependability tools are becoming an indispensable tool for modeling and analyzing (critical) systems. However the growing complexity of such systems calls for increasing sophistication of these tools. Dependability tools need to not only capture the complex dynamic behavior of the system components, but they must be also easy to use, intuitive, and computationally efficient. In general, current tools have a number of shortcomings including lack of modeling power, incapacity to efficiently handle general component failure distributions, and ineffectiveness in solving large models that exhibit complex dependencies between their components. We propose a novel reliability modeling and analysis framework based on the Bayesian network (BN) formalism. The overall approach is to investigate timed Bayesian networks and to find a suitable reliability framework for dynamic systems. We have applied our methodology to two example systems and preliminary results are promising. We have defined a discrete-time BN reliability formalism and demonstrated its capabilities from a modeling and analysis point of view. This research shows that a BN based reliability formalism is a powerful potential solution to modeling and analyzing various kinds of system components behaviors and interactions. Moreover, being based on the BN formalism, the framework is easy to use and intuitive for non-experts, and provides a basis for more advanced and useful analyses such as system diagnosis.     

The part mix and routing mix problem in FMS: a coupling between an LP model and a closed queueing network

In the near future many companies will face the problem of the optimal use of newly installed manufacturing technology (e.g. a flexible manufacturing system or FMS). Very often this will involve decisions on what parts to produce using the new system (the part mix problem) and how to produce these parts (the routing mix problem). We show that traditional operational research tools such as linear programming and queueing network theory are well suited to tackle these problems. In particular, LP models are combined with queueing network models in an iterative procedure. As such the strengths of both techniques can be exploited in making optimal use of the part mix and routing mix flexibility of the FMS.     

Integrating ABM/TOC approaches for performance improvement: A framework and application

During the last 20 years, new philosophies such as the Theory of Constraints (TOC) and Activity-Based Management (ABM) have emerged as viable, distinct alternatives for measuring and improving the performance of world-class manufacturing companies. In the early phase of their evolution, these philosophies differed fundamentally in their approaches; but there is increasing evidence that both philosophies have now evolved to a stage where an integrated framework can be developed for enhancing cross-functional coordination, thereby improving organizational performance. In this paper, a general framework is presented that integrates the basic concepts, as well as recent advances of TOC and ABM philosophies, into a cohesive framework that can be used to guide performance improvement initiatives . A successful implementation in a world-class manufacturing company is described to validate the framework and to demonstrate that these philosophies can indeed work together in positive ways. Insights are provided into the reasons for implementing such an integrative framework, e.g. identifying the most profitable mix of products, allocating scarce resources optimally, establishing priorities for process improvements, analysing the strategic investment (or expansion) alternatives, and exploiting new market segments.     

A decision support system for factory automation: a case study

Economic justification for factory automation (FA) and development of a decision support system (DSS) have recently been two independent ‘hot’ research topics. This paper integrates the two issues by developing the Decision Support System for Factory Automation (DSSFA) which follows generally accepted DSS framework and considers critical factors in justifying FA. Then, the DSSFA is applied to a real plant which is considering factory automation.     

Quantitative methodology for strategic assessment of the sustainability of bauxite residue management

Decisions on sustainable technologies are surrounded by high degrees of uncertainty and absence of agreed indicators and metrics. The alumina industry therefore supported the development of a quantitative methodology for strategic assessment of the sustainability of bauxite residue management. It combines a strategic outlook with quantitative, outcome-based assessment. The methodology compares current practice with ideal values, derived from sustainability aspirations. The indicator system combines management indicators (for planning, management and reporting systems); condition indicators (state of environment and communities surrounding residue operations); and operational indicators (technical and economic performance). They have three hierarchical levels: headline performance indicators (6, measuring sustainability objectives); key performance indicators (24, measuring sustainability impacts) and performance measures (flexible set, measuring operational contributions). Performance is measured on a five-level ordinal scale. The methodology was successfully piloted at an operating plant. This confirmed that the methodology complemented existing audit protocols and strategic planning processes. The unique advantages are the universal performance measuring system for environmental, social and economic outcomes, and the strategic orientation towards improvement and innovation in residue technology. This development demonstrates that even with imperfect knowledge and uncertainty, quantified sustainability tools can be developed that aid in decision making on technology development and implementation.