Launching and dispatching strategies for multi-criteria control of closed manufacturing systems with flexible routeing capability

In this paper, we study the problems of launching and dispatching of parts in closed manufacturing systems with flexible routeing. For the manufacturing systems being operated against multiple performance criteria, we postulate that controlling different aspects of the operational control strategy to meet one single performance criterion would improve overall system performance. It is suggested that to achieve production rates, launching rules be utilized and to affect flowtime, dispatching rules be manipulated. Also, for measurement of routeing flexibility, an entropic measure of flexibility is refined. The entropy-based rule is then compared with the dispatching rules commonly used in the industry. Control strategies are developed for a test system and it is shown that a hierarchical control strategy works best when multiple performance criteria are of interest.     

Product flexibility in selecting manufacturing planning and control strategy

The manufacturing systems capable of producing several products simultaneously are frequently subject to changes in product types due to demand fluctuations. In such systems a product flexible manufacturing planning and control (MPC) strategy is needed to change from one product type to another with minimum deterioration to system performance levels. The objective of this research is to develop a systematic analysis and evaluation approach in order to compare the MRP-push and JIT-pull strategies quantitatively based on a product flexibility measure. A new product flexibility measure is developed based on the sensitivity to change concept and presented together with the implementation in a real manufacturing system. Simulation is used to compare the performance of a JIT-pull with an MRP-push strategy based on performance measures, e.g. manufacturing lead time, work-in-process inventory, backorders, machine utilization and throughput. The performances of the two strategies are evaluated in two scenarios: (i) a single product; (ii) a second product is added (the first product being simple and the second being complex in terms of processing). The impacts of adding the second product on the performance measures for the push and pull strategies are then assessed. A multi-attribute evaluation scheme is used to compare the two strategies where the attribute values are the change in performance measures as the second product is added. The proposed product flexibility measure is utilized in the interpretation of the results.     

Conceptualizing manufacturing flexibility: An operational approach and a comparative evaluation

An operational approach to conceptualization and the measurement of manufacturing flexibility is presented. A critical review of selected measures from the literature is provided in the context of the operational approach. A flexibility measure is proposed. A formulation and the features of the proposed measure are discussed. An application of the measure is demonstrated through a hypothetical example. Using the same example, selected flexibility measures from the literature are evaluated. The performance of the measures and the proposed measure are compared.     

A note on: On controlling the controllable lead time component in the integrated inventory models

This paper develops an analytical approach to quantifying manufacturing system flexibility (MSF). Measures of flexibility, namely, producibility, processivity, transferability and introducibility are developed based on a state-transition formalism, the reachability graph. The uncertainty in system operating conditions is specified in terms of certain disturbing factors, external and internal to the system, which impinge on system performance. The contribution of each factor to the value of a given type of flexibility is estimated using the analytic hierarchy process (AHP). The individual flexibility measures are thus combined to give a measure of MSF under a given operating environment. A Petri net model is used to construct the reachability graphs used in flexibility measurement. Uses of the proposed measures at the design and operational analysis stages of FMS are presented     

Flexibility in manufacturing enterprises

A manufacturing enterprise is a collection of interrelated, flexible, optimized business processes delivering value to the customers through high quality products and services, faster than competition. This view of an enterprise enables one to consider the entire business system including the suppliers, product development, manufacturing, logistics, distribution, and retailing and to smoothen out the interfaces between them. Performance measures and performance measurement are important for monitoring, control and management. We identify and discuss eight performance measures for generic business processes. These include lead time, customer service, dependability, quality, flexibility, cost, capacity, and asset utilization. In this paper, we concentrate on flexibility of business processes with special emphasis on the supply chain and order-to-delivery processes. We attempt to provide clear definitions and measures of various types of flexibilities as well as discuss the relationship between product structure and supply chain flexibility. The relationship between uncertainties, flexibility, technology, and product structure is clearly brought out in this paper.     

Entropic measures of manufacturing flexibility

Axiomatic approach to develop an objective theory of flexibility in manufacturing system is presented. On the basis of some plausible axioms for a measure of flexibility, we suggest some information theoretie measures to quantify various types of flexibility. Four entropic measures are identified and the model illustrations for computations are given.     

Quantifying machine flexibility

There are several studies aiming to quantify several aspects of flexibility in manufacturing systems like routing flexibility, product mix flexibility, volume flexibility, etc. However, there is still a need to develop more generic measures that can be used to quantify flexibility of systems in order to enable decision-makers to reach better decisions in selecting between different system configurations. In this study, a new approach which is based on digraph theory and matrix algebra is proposed to quantify flexibility. Several examples are also provided to illustrate the proposed approach and its practicality and usefulness. The proposed approach is a novel one and can be used to model and quantify several types of flexibilities. In this research, the proposed modelling approach is explained through machine flexibility mainly due to the fact that most of the other flexibility types in manufacturing systems rely on this flexibility type.     

Flexibility-enabled lead-time reduction in flexible systems

This paper presents the results of a conceptual study and simulation experimentation aimed at understanding the underlying mechanisms of sequencing flexibility-enabled manufacturing lead-time reduction. In spite of a large body of literature on flexibility, the exact mechanism that enables flexibility to reduce the lead time is not fully understood. As a part of our research efforts on the proactive application of flexibility for the performance enhancement of manufacturing systems, we are motivated to study how flexibility can be employed in a proactive manner to reduce the manufacturing lead time and to develop an understanding of the underlying mechanisms. Towards this end, we have developed simulation models of simple flexible manufacturing systems and studied the effect of sequencing flexibility on the lead-time performance under different conditions of part load and machine load balancing. The studies indicated that sequencing flexibility has a significant effect on the lead-time performance of the manufacturing system, and the effect of flexibility varies under different conditions of load balancing. Further studies indicate the existence of complex interactions between the sequencing flexibility, process concurrency, processor load balancing, and manufacturing lead time. This paper intends to discuss some of the interesting results of these studies with a focus on the inherent mechanisms of sequencing flexibility-enabled lead-time reduction.     

A new method for guiding process flexibility investment: flexibility fit index

Flexibility enables manufacturing firms to respond efficiently to changes in the environment. Many firms make great efforts to increase their manufacturing flexibility to remain competitive in today's turbulent market. However, it is not true to say that the more flexible the better, because the cost of flexibility investment is high, and the capital for flexibility investment is limited. In this paper, we present a new method to guide process flexibility investment by developing a flexibility fit index. Taking demand changes into account, our method first defines a measure to quantify the requirement level of process flexibility. Then, a flexibility fit index is defined, which specifically identifies where flexibility is insufficient and where flexibility is surplus for a manufacturing system operating in a changing environment. The proposed fit index is objective and dimensionless, and so can be used more universally than previous subjective or non-dimensionless measures proposed in the literature. A set of simulation experiments shows that the proposed method can better guide flexibility investment by indicating the system structure which fits best with a given business situation, and other measures that ignore demand information may lead to over-investment or adding links that bring little benefit.     

On measurement and valuation of manufacturing flexibility

The concept of flexibility has been a recurring theme in recent manufacturing literature. Manufacturing flexibility is widely acclaimed as a formidable competitive weapon in the arsenal of any manufacturing firm. Yet critical underpinnings of this concept are not well understood despite efforts by various researchers to classify different flexibility types in order to facilitate its measurement and valuation. This paper examines reasons why measurement of flexibility has remained difficult. It proposes that any measure must inevitably depend on factors such as the degree of uncertainty in the environment, management objectives, machine capabilities and configuration (control). Therefore it advocates surrogate measures such as the value of flexibility. A model illustrating how flexibility might be measured and its appropriate level chosen, in a specific scenario, is presented. Numerical examples reveal additional insights that might be useful to firms with characteristics that match those of the model.     

制造柔性的概念框架及其度量

研究了制造柔性的概念，讨论了制造柔性的特点及其对制造系统综合运行性能的影响，提出了一个用于对制造柔性进行分类的概念框架，探讨了制造柔性的度量方法。     

A methodology for monitoring system performance

Monitoring and improving manufacturing processes involves identifying, investigating and eliminating problems responsible for inefficiencies in production operations. While statistical process control tools, such as control charts, are available for process monitoring at the operational level, methods for evaluating system performance from more strategic and tactical levels are limited. The traditional control charts that monitor a single process parameter at a time may not be appropriate in situations where interrelationships among various system measures exist. Although multivariate process control techniques allow for simultaneous monitoring of several process parameters, they require assumptions of independence and multivariate normality of data. In addition, their application has mostly been at an operational level. In order to assist managers in monitoring and improving manufacturing system performance, this paper proposes an individual control chart that monitors an integrated performance index generated from a non-parametric method, which effectively considers multiple performance measures and the relationships between them. The primary advantages of this method are that a single integrated measure can be monitored, does not require assumptions of independence and multivariate normality of data, and allows for the integration of decision-maker's input when the system measures that are monitored have unequal importance.     

Managing demand variability using requisite variety for improved workflow and operational performance: the role of manufacturing flexibility

In this study, we use the law of requisite variety to investigate the effect of manufacturing flexibility on workflow and operational performance. After developing a requisite variety construct using a parsimonious conceptualisation of manufacturing flexibility, we test our research model with data collected from US manufacturers. The results of the analysis using structural equation modelling support our hypotheses. Our study makes three important contributions. First, we provide a more complete understanding of manufacturing flexibility and its relationship to operational performance. By empirically testing our model, we develop support for manufacturing flexibility as a workflow regulator which provides an organisation with the necessary variety in its response-repertoire to effectively manage demand variability. Second, our analysis of our requisite variety construct allows us to better understand the complex relationship between manufacturing flexibility and efficiency. Our findings suggest that the trade-off between manufacturing flexibility and efficiency can be attenuated. Third, we provide evidence to show that manufacturing flexibility positively influences performance by increasing the speed of material flow and improving organisational efficiency.     

Managing worker flexibility and attrition in dual resource constrained job shops

Worker flexibility is an attractive option for enhancing manufacturing performance, since it provides several strategic advantages, and also allows the firm to buffer against uncertainty. In this paper, we investigate issues related to acquiring a flexible work-force in those dual resource constrained (DRC) job-shops that have high learning costs and the presence of worker attrition. Our results show that significant improvement in traditional shop related measures can be attained at even very high attrition rates by incrementally training each worker in one additional department. However, this improvement comes at the expense of productivity losses which shop managers may not be willing to accept. The nature of the tradeoffs that exist in acquiring this incremental worker flexibility are addressed. Two strategies for improving shop performance, based on incrementally training workers or reducing attrition rates, are also recommended for the DRC shop modelled in our study. Conditions under which either of these two strategies should be pursued by the shop managers are also identified.     

An approach to the measurement of single-machine flexibility

Flexibility of manufacturing systems has been recognized as one of the vital competitive priorities in manufacturing strategy. However, the meaning and implementation of flexibility remain blurred. The main reason could be that the attributes of manufacturing system flexibility are many and complicated. This research suggests that there are at least two factors that should be considerednamely, efficiency and versatility-in the measurement of manufacturing flexibility. The entropy approach, which was extended from information theory and has been applied comprehensively in the research of market diversity in the economics field, has its limitations in the measurement of manufacturing flexibility. It depicts only the factor of versatility, and not that of efficiency. This research proposes a combination of the entropy approach and the efficiency frontier approach, Data Envelopment Analysis (DEA), for the measurement of manufacturing flexibility. This approach has been applied to the measurement of single machine flexibility and a straightforward example is exhibited in this research.     

Effectiveness of planning and control systems: An empirical study of US and Japanese firms

Both researchers and practitioners have investigated the effectiveness of manufacturing planning and control systems (MPCS) in an attempt to justify the investment in MPCS. This study uses the Wight's (1981) detailed questionnaire to measure the degree of planning and control implementation in a manufacturing system, which is referred to as MPCS rating. The MPCS rating is then used to study the relationship between the self-assessed manufacturing competitiveness (cost, quality, delivery and flexibility) and the objective performance measures of manufacturing performance such as production cost, productivity change, customer reject percent, manufacturing lead time, etc. The results show that there is a strong relationship between MPCS ratings and objective performance measures as well as self-assessed competitiveness in both Japanese and US firms. The results are important since they indicate that fundamental manufacturing planning and control procedures improve a firm's performance on both its internal operations as well as external competitiveness goals.     

A stochastic model of a reconfigurable manufacturing system - Part 4: Performance measure

Various products required by customers are classified into several product families, each of which is a set of similar products. A reconfigurable manufacturing system (RMS) manages to satisfy customers, with each family corresponding to one configuration of the RMS. Then, the products belonging to the same family will be produced by the RMS under the corresponding configuration. The manufacturing system possesses the reconfigurable function for different families. A performance measure is defined as service levels for the families. A semi-Markov process is formulated for obtaining the performance measure. When a larger fluctuation in the market happens, the manufacturer can adjust the system to improve the performance measure. An optimization of a reassigning problem is discussed, which reassigns the maximum numbers of orders to the families. Two solution approaches are proposed to solve the problem. Numerical examples are given for illustrating the methodologies.     

The effect of routing flexibility on a flexible system of integrated manufacturing

Flexible manufacturing systems (FMSs) have gained consideration due to their ability to produce customised and an increasing variety of products with shorter life cycles. A considerable amount of research has been done on manufacturing flexibility from different angles. There are many different types of manufacturing flexibility being reported in the literature, and routing flexibility is one of them. The paper focuses on the study of routing flexibility in a flexible system of integrated manufacturing (FSIM) from the view of real-time control strategies. However, flexibility incurs cost hence a judicious decision is required for implementing the right level of flexibility under a different operating environment. The paper studies the impact of routing flexibility and control strategies on the performance of FSIM. The application of discrete event simulation and Taguchi's method is applied to study the various factors contributing to FSIM performance and identifies the vital parameters for improving performance. Furthermore, the most significant factor is determined by using the analysis of variance (ANOVA). The result shows that increasing routing flexibility cannot be treated as a key role in system improvement. It is also found that there is the influence of control strategies on the performance of FSIM. Finally, it is observed that, the impact on the system performance due to the system load condition is the largest, and that of the number of pallets is the smallest.     

A stochastic model of a reconfigurable manufacturing system Part 1: A framework

Products required by customers are classified into several product families, each of which is a set of similar products. A reconfigurable manufacturing system (RMS) manages to satisfy customers, with each family corresponding to one configuration of the RMS. Then the products belonging to the same family will be produced by the RMS under the corresponding configuration. The manufacturing system possesses the reconfigurable function for different families. In an RMS there are three important issues: the optimal configurations in the design, the optimal selection policy in the utilization, and the performance measure in the improvement. This paper proposes a framework for a stochastic model of an RMS, which involves the above issues. Two optimization problems and the performance measure stemmed from the issues are formulated. An example is given for illustration. Some discussions are presented for future research work.     

A new grouping measure for evaluation of machine-component matrices

The machine-component matrix is the main input to most machine-component grouping models used in cellular manufacturing. A number of measures have been developed for performance evaluation of machine-component grouping algorithms. In this paper, the relationship between these measures and the performance of the corresponding cellular manufacturing system is evaluated and a new grouping measure is developed which is more consistent in predicting the suitability of a manufacturing system for cellular manufacturing.