A Citation Analysis of the Research on Manufacturing and Supply Chain Flexibility

Manufacturing and supply chain flexibility has been discussed extensively in the scientific literature. Given the different definitions, types and dimensions of flexibility, the purpose of this paper is to explore the origins and structure of the scientific research on manufacturing and supply chain flexibility. We identified a sample of 153 internationally published papers and conducted a citation analysis to examine the connections between the many scientific papers and to explore the most influential works and their impact on flexibility research. Our analysis revealed that research on flexibility received the most scientific attention between 1996 and 2005. However, the majority of the currently valid types and dimensions of flexibility have been defined in the late 1980s and the early 1990s. The current paper provides the leading academic journals and papers in the field of flexibility research. Additionally, the results of our citation analysis indicate that flexibility research is significantly influenced by papers that have been presented at subject-specific conferences. Finally, our paper presents a clearly arranged structure of the most frequently cited papers dealing with manufacturing and supply chain flexibility. Furthermore, its contents and findings are briefly discussed to provide an overview of the previous academic research.     

Process flexibility under bill of material constraints: part II–structural properties and improving principles

For the manufacturing system that consists of multiple assembly lines, this paper investigates the method of improving its process flexibility under bill of material (BOM) constraints. Based on the flexibility measurement developed in part I, generic characteristics of the capability configuration of assembly lines that ensure it more flexible are first investigated on two hierarchical and highly interrelated levels: the assembly line level and the system level. These characteristics are termed ‘structural properties’ of process flexibility under BOM constraints, which are valuable because they provide an effective way of improving flexibility of the manufacturing system through investing in limited operational flexibility of machines in the assembly lines. According to the obtained structural properties, guidelines for improving process flexibility on the two levels are then developed. The proposed guidelines can help the manager of a manufacturing system to make effective decisions on flexibility improvement without much computation effort. Results of simulation experiments illustrate that the proposed structural properties and guidelines are effective and widely applicable to real manufacturing systems.     

Prioritising the types of manufacturing flexibility in an uncertain environment

Researchers have stressed that manufacturing system flexibility research requires a quantitative model allowing a manufacturing system to prioritize its flexibility dimension and promote the performance of the manufacturing system. A quantification model presented in the present research is demonstrated to assess the degree of environmental uncertainty and illustrates a method for delivering the requirement of flexibility improvement for the manufacturing system so that the company is able to prioritize the types of manufacturing flexibility which a manufacturing system requires in an uncertain environment. Quantitative approaches including quality function deployment (QFD), analytical hierarchy process (AHP), and grey relational analysis (GRA) have been employed to find a means for improving the flexibility of a manufacturing system to cope with environmental uncertainty. QFD is the focal approach for the deployment of the integrated structure of the research. AHP is applied to explore the relative weighted importance of environmental uncertainty factors, while GRA is used to find out the relationships between manufacturing flexibility and environmental uncertainty. A combination of these approaches reveals a useful tool for managers to prioritize the types of flexibility which a manufacturing system requires for coping with an uncertain environment. In particular, the present research studied the manufacturing flexibility requirements of a food company in Taiwan.     

Measuring machine and product mix flexibilities of a manufacturing system

This paper provides a brief discussion on flexibility concepts in manufacturing. It emphasizes that flexibility measurements in a manufacturing system should be studied under dynamically changing environments rather than static ones. The approaches for assessing two major flexibility types, machine flexibility and product mix flexibility response, are presented. The machine flexibility model is based on machine-operation efficiency. The product mix flexibility response model is based on the difference between products in terms of tooling requirements, the number of operations that a machine can perform and the efficiency of different machines.     

Modelling and integration of customer flexibility in the order commitment process for high mix low volume production

With increasing product variety and dynamic demand fluctuation, manufacturing industry is moving towards a high product mix and low order volume production environment. Consequently, the order commitment process is becoming one of the most important processes for manufacturing firms to meet individual customer's needs with limited resources. However, demands for shortened delivery lead time, diverse customer requirements and more frequent customer orders have made the order commitment task more challenging. This paper attempts to tackle these new challenges by incorporating not only manufacturing flexibility but also flexibility from the demand side. Customer flexibility is characterised by customer indifference to certain product attributes and/or delivery schedules. Intuitively, with the consideration of customer flexibility, both manufacturers’ and customers’ interests can be better served since the solution space of matching demand and supply can be extended beyond the traditional domain purely from a manufacturing perspective. To this end, a systematic approach is developed to characterise and model customer flexibility. A mixed-integer-programming model is formulated to provide optimal order commitment decisions.     

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.     

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.     

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.     

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.     

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.     

企业柔性:基于集成的观点

从集成的思想出发分析了柔性的内涵，认为企业柔性的目标是提高企业在动态环境条件下的整体竞争优势，柔性的基础是在更大范围内的协调优化与有效集成；从系统的角度将企业柔性分为市场柔性，研发柔性，制造柔性与组织柔性四个维度，对每个维度所包括的具体内容进行了分析；建立了企业柔性的概念模型，从整体的角度出发对企业的柔性的形式与作用机制进行了描述。     

The influence of manufacturing flexibility on the interplay between exploration and exploitation: the effects of organisational learning and the environment

This paper analyses whether the firm can combine exploration and exploitation and seeks to determine whether implementing manufacturing flexibility will facilitate the development of either of these two terms or both simultaneously. This relationship was measured in 231 Spanish production firms. The results obtained show that: (1) firms develop exploration of new knowledge at the same time as they exploit their abilities; (2) manufacturing flexibility encourages the development of both exploration and exploitation; (3) this relationship is even more significant if we take into account dynamism of the environment and organisational learning.     

Conceptualising complementarities in manufacturing flexibility: a comprehensive view

In this paper, we develop an extended view of the manufacturing flexibility construct. Instead of a sequential view as emphasised with the competence-capability perspective, the model presented in this study suggests a holistic view of manufacturing flexibility comprised of six complementary dimensions. We contend that the complementary view of manufacturing flexibility (MFLX) consisting of six dimensions – product-mix flexibility (PMX), routing flexibility (RTG), equipment flexibility (EQP), volume flexibility (VOL), labour flexibility (LBR), and supply management flexibility (SPM) – provides a path to implementation of manufacturing flexibility. Manufacturing flexibility is hypothesised as a second order construct comprised of the six complementary dimensions. We test our proposed model using data collected from US manufacturing organisations. Structural equation modelling was used to analyse the data. The results of confirmatory factor analysis support our hypothesis of a second order multi-dimensional construct structure. This comprehensive conceptualisation of manufacturing flexibility should help researchers evaluate the effect of manufacturing flexibility on operational and financial performance.     

Firms’ integrating efforts to mitigate the tradeoff between controllability and flexibility

We consider three manufacturing capabilities: controllability, flexibility, and integrating capability. Controllability is a firm's ability to control its process to enhance efficiency and accuracy and to better meet specifications. Flexibility is a firm's ability to cope with uncertainty and variation, both internal and external. Integrating capability is a firm's ability to integrate and coordinate diverse functions and parts of its supply chain, embodied in overall operations effectiveness and new product innovation. We put forth two hypotheses. First, there is an inherent tradeoff between controllability and flexibility. Second, a firm's integrating effort across its supply chain enables it to overcome such a tradeoff, making it possible to improve both controllability and flexibility simultaneously. Using data from 193 manufacturing companies, we test our hypotheses. It turns out that the relationship between controllability and flexibility is convex-shaped, indicating there are two distinct regions: one in which the relationship is negative and the other, positive. Further, the firms in the positive relationship region make significantly more effort to integrate, that is to say coordinate and communicate, across their supply chains, implying that as the firm strives to integrate its supply chain functions, it can mitigate the tradeoff between controllability and flexibility to a considerable extent.     

IT能力对竞争优势的影响机制:以制造柔性为中介

为研究IT能力对企业竞争优势的影响机制,以制造柔性为中介变量,运用结构方程模型对来源于珠三角地区制造企业的381份调查数据进行了实证分析。研究结果表明,IT能力对制造柔性具有显著的正向影响,制造柔性对企业竞争优势也有显著的正向影响。此外,制造柔性在IT能力与竞争优势的关系起着显著的部分中介作用,并且IT能力通过制造柔性对竞争优势的影响效应占总效应的44.3%。     

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.     

An impact of manufacturing flexibility and technological dimensions of manufacturing strategy on improving supply chain responsiveness: Business environment perspective

The main objective of this research is to investigate the impact of manufacturing flexibility and technological dimensions of manufacturing strategy on responsiveness in the supply chain. Based on the theoretical background of dynamic capability, this study also examines the role of the business environment on the relationship between manufacturing flexibility and supply chain responsiveness. 144 structured surveys were collected and the partial least squares of structural equation modelling approach were utilised for data analysis. The result establishes relationships among various dimensions of manufacturing flexibility. Although the technological dimensions in manufacturing strategy of such advanced manufacturing technology (AMT) and e-procurement do not have any direct impact on new product and market flexibility, they increase supply chain responsiveness, which helps to react quickly against supply chain disruptions. More importantly, the business environment has a moderating effect on the relationship between market flexibility and supply chain responsiveness.     

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.     

Model for flexibility evaluation in manufacturing network strategic planning

In response to market pressures, manufacturers have adopted different approaches to provide flexibility regarding several aspects. In this paper, we suggest a model for the evaluation of the flexibility of the manufacturing supply chain, based on graph theory techniques. This model defines maximum excess demand that may be met using flexibility. Recourse to flexibility enablers is determined based on cost minimisation. Such enablers are volume flexibility, mix flexibility and safety stocks. The proposed model is solved using a two-step Mix Integer Linear Programme; the first step consists in defining maximum demand that may be met while the second step concerns minimising cost. The main benefit of our model is to deal with realistic problems in a rather short time. Therefore, it can be used in a wide ‘what-if’ design process. It means evaluating various contemplated flexibility configurations in multiple demand scenarios in order to choose the best option. It can be also used during operational supply chain planning in order to face to an unbalanced situation. This paper ends with a numerical example illustrating our model’s efficiency.     

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.