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.     

Dynamic lot size/sequencing policies in a multi-product,single-machine system

This paper is concerned with the modeling and analysis of a single-machine, multi-product, integrated production–inventory system. A semi-Markov model is developed that incorporates a state-dependent control system. Control optimization is achieved through the use of Markov-renewal programming. Three- and four-product models are developed. The model(s) are exercised over a range of parameters in order to determine the characteristics of the system, and to identify the structure of the optimal control rules of the system. The result is that one can identify simple basic rules of operation that are near-optimal in a dynamic environment, and that make sense intuitively.     

The effects of routing flexibility in a multi-stage pull-type system

The pull-type manufacturing system is known for its need for a frozen schedule, balanced work load and inability to handle fluctuations in demand. But today research and development are addressing ways to handle a pull-type system to accommodate greater fluctuations. One approach is to design the system with machines that have a greater routing flexibility in what work they can perform. However, most of the existing literature dealing with routing flexibility has primarily been devoted to the push-type production systems. This research examined the effects of routing flexibility for a multi-stage kanban-controlled pull-type system.     

Flowshops with processing flexibility across production stages

This paper addresses a scheduling problem for a two stage hybrid flowshop (HFS) environment with significant processing flexibility across stages. A job can be either completely processed at one of the stages or its processing is split in a prespecified fashion between stages. For the latter case, the routing is only in one direction, from the 'upstream' stage to the 'downstream' stage. A stage may consist of one or more parallel identical machines. We first study the special case of a single machine per stage and present a pseudopolynomial dynamic programming algorithm to minimize makespan. Then, we provide a heuristic for the HFS_m1,m2 problem with m_k machines at stage k = 1,2, and prove its worst case and average performance. Also, we extend our algorithms to the case of stage dependent processing times. Finally, we report computational results on the average performance of HFS_m1,m2 with comparable flowshop and parallel machine environments, and provide managerial guidelines for process choice decisions.     

Structural flexibility indices with shrinking capacities in cross production

This paper examines structure indices for process flexibility planning with efficiency loss in cross production. We generalise the Structural Flexibility Index and the Graph Expander Index by incorporating shrinking capacity factors. These two deterministic indices are computationally tractable and they allow for simple analysis of alternative system designs. Therefore, they can help design an effective flexibility structure without extensive simulations. Numerical experiments show that both indices can predict the flexibility performance of various system structures.     

Analytical models to predict the performance of a single-machine system under periodic and event-driven rescheduling strategies

This article presents initial results in the search for analytical models that can predict the performance of one-machine systems under periodic and event-driven rescheduling strategies in an environment where different job types arrive dynamically for processing and set-up must incur when production changes from one product type to another. The scheduling algorithm considered uses a first-in firstout dispatching rule to sequence jobs and it also groups jobs with similar types to save set-up time. The analytical models can estimate important performance measures like average flow time and machine utilization, which can then be used to determine optimal rescheduling parameters. Simulation experiments are used to show that the analytical models accurately predict the performance of the single machine under the scheduling algorithm proposed.     

Layout optimization considering production uncertainty and routing flexibility

The unequal area facility layout problem is studied considering both production uncertainty and routing flexibility. Stochastic production quantities are introduced under the assumption of dependent demands and incorporated into the usual objective of material handling cost minimization. Concurrently, alternative routings are considered based on production quantity. An efficient simulation approach is used to estimate the resulting department pairwise flows, both their expected values and variances. Using these estimates, a tabu search heuristic procedure performs the layout design optimization.     

Quantifying the advantages of production quota flexibility in the automotive industry

Manufacturers use production quotas to smooth and synchronize production. We use a Markov chain to quantify the effect of quota flexibility on overtime and inventory costs. This quantification allows us to trade off these costs to find the optimal amount of quota flexibility. We define quota flexibility as the permitted amount and duration of deviations from the cumulative quota. We specifically analyse the cost savings as a function of the maximum allowed deviation amount from the cumulative quota for four policies. These example policies are the four permutations of two factors: whether or not backlogging is permitted; and whether or not actual production and the quota must be reconciled weekly. We apply the model to three automotive assembly plants and conclude that permitting modest flexibility in production quotas (of ? 1 h of production) significantly reduces total cost.     

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.     

Selection of a pull production control system in multi-stage production processes

In this paper, we conduct an analytical comparison of three pull production control systems: Kanban, CONWIP and Base-stock in multi-stage production processes. First, we compare the three control systems in a multi-stage serial production process. Then, we compare them in multi-stage assembly production processes, and present guidelines that allow us to select the best system. As a result, we show which structural parameters decide the superiority of one control scheme to the others, and how they are related. A key for superiority is a configuration of parameters, such as processing times and number of cards employed in the system. We show that there is no general superiority amongst the analysed concepts. Finally, we verify the effect of variability on the system performance, and generalise the analytical results of deterministic cases by conducting numerical experiments.     

Factory design and process optimisation with flexibility measurements in industrial production

Manufacturing companies operate in increasingly turbulent and discontinuous environments. Uncertain projections regarding future sales, large volume fluctuations, the steady advance of new technologies, and ever-shorter product life cycles, combined at the same time with increasing product variety, demand the constant adjustment of production structures to meet the current market requirements. Uncertainty in the production area requires a continuous transformation of production structures to meet the current requirements on the market. This poses a challenge for manufacturers in the various branches of industry and creates an ever-increasing need for flexibility to find an economic balance, in times of tight budgets, between the prevailing market uncertainties and the correct arrangement of the production systems. In the following document, the applied experience is presented, extracted from the flexibility assessment tool economical flexibility measurement (ecoFLEX). It will be shown along with the practical experience gained in its application at a car-engines plant.     

Cellular manufacturing systems design with routing flexibility,machine procurement,production planning and dynamic system reconfiguration

This paper investigates the problem of designing cellular manufacturing systems with multi-period production planning, dynamic system reconfiguration, operation sequence, duplicate machines, machine capacity and machine procurement. An important aspect of this problem is the introduction of routing flexibility in the system by the formation of alternate contingency process routings in addition to alternate main process routings for all part types. Contingency routings serve as backups so as to effectively address the reality of part process routing disruptions (in the main routings) owing to machine breakdowns and allow the cellular manufacturing system to operate in a continuous manner even in the event of such breakdowns. The paper also provides in-depth discussions on the trade-off between the increased flexibility obtained versus the additional cost to be incurred through the formation of contingency routings for all parts. Some sensitivity analysis is also performed on some of the model parameters. The problem is modelled and solved through a comprehensive mixed integer programming formulation. Computational results presented by solving some numerical examples show that the routing and process flexibilities can be incorporated within the cellular manufacturing system design without significant increase in the system cost.     

Strategies for evaluating performance of flexibility in product recovery system

In view of the increasing business opportunities with changing customer attitudes and stricter legislations, the handling of returns has become a daunting challenge. The need for decision models for evaluating return performance has been observed in the academia and the corporate world. To improve return system performance, integrated flexible reverse enterprise systems have attracted attention from researchers as well as practitioners. This paper addresses these critical issues and proposes a novel integrated and Flexible recovery system decision model. The proposed model aims to facilitate enterprises in assessing their product recovery system capability, and in improving overall performance. The proposed model is a natural extension of several well-grounded policies for conventional reverse supply chains and can be verified on a simulation platform.     

A large-scale distributed decision-making procedure for a single-machine scheduling problem

This paper presents a distributed scheduling procedure for a large-scale single-machine problem with precedence constraints, and identifies phenomena using large-scale distributed decision-making for a decomposable and distributed situation. The approach proposed exhibits efficient computational performance over a large-sized work load (23,000 jobs and 2,209,536 precedence constraints) in a distributed computing environment. We highlight three findings: (1) the communication burden originating from the large-scale problem can lead to performance loss while distributed agents collaborate to solve the problem, but after a threshold the computational gain by distribution offsets the loss; (2) when the problem size is sufficiently large, the real computation gain outperforms the expected gain by the number of agents (super-linear effect); and (3) when the number of precedence constraints of each agent differs, the slowest agent processing the largest number of precedence constraints restrains the computational performance (load imbalance). We believe that our research is the first distributed decision-making model that meets the requirements of distributed information, distributed decision authority, and distributed computation in a large-scale single-machine scheduling situation with precedence constraints.     

Batch sizing with controllable production rates in a multi-stage production system

In this paper, a comprehensive model is presented for cell formation and layout design in cellular manufacturing systems (CMS). The proposed model incorporates an extensive coverage of important operational features and especially layout design aspects to determine optimal cell configuration and Intra and Inter-cell layout in CMS. Hence, proposed integrated approach attempts to design intra and inter-cell layout and material handling flow path structure simultaneously. We examine the great potential benefits of providing these features consist of routing flexibility, operation sequence, machine capacity, considering number of cells as a decision variable, un-equal dimension of machines, free machines and cells orientation, and considering pickup and drop off station for each cell. In order to show the effects and important of integrated design in the CMS, two approaches, sequentially and integrated, have been investigated and demonstrate the integrated approach improve the quality of obtained solution. The proposed model is a mixed integer non-linear programme. Linearisation procedures are proposed to transfer it into a linearised mixed integer programming formulation. Computational results are presented with the linearised formulation. We presented several enhancements in terms of valid inequalities and extensions to the proposed model in order to improve its computational performance. Finally, concluding remarks are provided.     

Integrated maintenance and production control of a deteriorating production system

We consider a make-to-stock production/inventory system consisting of a single deteriorating machine which produces a single item. We formulate the integrated decisions of maintenance and production using a Markov Decision Process. The optimal dynamic policy is shown to have a rather complex structure which leads us to consider more implementable policies. We present a double-threshold policy and derive exact and approximate methods for evaluating the performance of this policy and computing its optimal parameters. A detailed numerical study demonstrates that the proposed policy and our approximate method for computing its parameters perform extremely well. Finally, we show that policies which do not address maintenance and production control decisions in an integrated manner can perform rather badly.     

Aggregate production planning in the automotive industry with special consideration of workforce flexibility

We present a new mixed integer linear programming approach for the problem of aggregate production planning of flowshop production lines in the automotive industry. Our model integrates production capacity planning and workforce flexibility planning. In contrast to traditional approaches, it considers discrete capacity adaptations which originate from technical characteristics of assembly lines as well as from work regulations and shift planning. In particular, our approach takes change costs into account and explicitly represents a working time account via a linear approximation. A solution framework containing different primal heuristics and preprocessing techniques is embedded into a decision support system. Finally, we present an illustrative case study and computational results on problem instances of practically relevant complexity.     

Using cognitive work analysis to explore system flexibility

The presented work describes a structured approach for identifying flexible working practices in complex socio-technical systems; further, it presents a framework for the elicitation of design changes capable of increasing system adaptability. The proposed approach uses the first three phases of the cognitive work analysis framework: work domain analysis; control task analysis; and strategies analysis. Functions are extracted from an abstraction hierarchy; these are then explored in a number of different situations using a contextual activity template. These functions are then explored in greater detail with the strategies analysis phase. The contextual activity template is used to identify situations where functions are unable to perform; in order to increase the flexibility of the system, new strategies are then proposed and represented in strategies analyses flow diagrams. To communicate the approach, it is introduced using the familiar, domestic domain of an ‘Apple iPod’. The paper presents a structured approach based upon cognitive work analysis for exploring system flexibility. The case study presented, an Apple iPod, shows how design changes to the system can be informed by this approach. This paper takes an existing approach and clarifies the link between analysis and design.