Showing papers in "International Journal of Production Research in 2016"

A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory industry 4.0

Abstract: Smart factories Industry 4.0 on the basis of collaborative cyber-physical systems represents a future form of industrial networks. Supply chains in such networks have dynamic structures which evolve over time. In these settings, short-term supply chain scheduling in smart factories Industry 4.0 is challenged by temporal machine structures, different processing speed at parallel machines and dynamic job arrivals. In this study, for the first time, a dynamic model and algorithm for short-term supply chain scheduling in smart factories Industry 4.0 is presented. The peculiarity of the considered problem is the simultaneous consideration of both machine structure selection and job assignments. The scheduling approach is based on a dynamic non-stationary interpretation of the execution of the jobs and a temporal decomposition of the scheduling problem. The algorithmic realisation is based on a modified form of the continuous maximum principle blended with mathematical optimisation. A detailed theoretical analy...

Additive manufacturing technologies: state of the art and trends

Abstract: The rapid prototyping has been developed from the 1980s to produce models and prototypes until the technologies evolution today. Nowadays, these technologies have other names such as 3D printing or additive manufacturing, and so forth, but they all have the same origins from rapid prototyping. The design and manufacturing process stood the same until new requirements such as a better integration on production line, a largest series of manufacturing or the reduce weight of products due to heavy costs of machines and materials. The ability to produce complex geometries allows proposing of design and manufacturing solutions in the industrial field in order to be ever more effective. The additive manufacturing (AM) technology develops rapidly with news solutions and markets which sometimes need to demonstrate their reliability. The community needs to survey some evolutions such as the new exchange format, the faster 3D printing systems, the advanced numerical simulation or the emergence of new use. This revie...

A survey on dynamic and stochastic vehicle routing problems

Abstract: Research on dynamic and stochastic vehicle routing problems received increasing interest in the last decade It considers a novel problem class, aiming at an appropriate handling of dynamic events combined with the incorporation of stochastic information about possible future events This survey summarises the recent literature in this area Besides, the classification according to the available stochastic information, a new classification based on the point in time where substantial computational effort for determining decisions or decision policies arises, is introduced Furthermore, the difference in solution quality is analysed between approaches which consider either purely dynamic or stochastic problems compared to those which consider both, stochastic and dynamic aspects A graphical representation demonstrates the strength of the reviewed approaches incorporating dynamic and stochastic information The survey also gives an overview on the intensity of research for the different problem classes and

Sustainable supplier management – a review of models supporting sustainable supplier selection, monitoring and development

Abstract: In the last two decades, pressure from various stakeholders has forced many companies to establish environmental and social improvements both in their company and their supply chains. The growing number of journal publications and conference proceedings confirms this change also in academia. The aim of this paper is to analyse and review scientific literature on sustainable supplier management (SSM) with a focus on formal models supporting decision-making in sustainable supplier selection, monitoring and development. For this purpose, a framework on SSM is proposed and a comprehensive content analysis including a criteria analysis is carried out. Beyond this, in total 143 peer-reviewed publications between 1997 and 2014 have been analysed to identify both established and overlooked research fields. Major findings are the rapidly growing interest of this topic in academia in recent years, the predominance of Analytic Hierarchy Process, Analytic Network Process and fuzzy-based approaches, the focus on the f...

Critical success factors for implementing lean production: the effect of contingencies

Abstract: To facilitate the implementation of lean production, practitioners and researchers have suggested an array of critical success factors (CSFs). However, despite a broad consensus about what needs to be done, companies still struggle to implement lean. Contingency theory posits the explanation that the common advice is not universal but is instead contingent on the situation. This paper investigates how contingency variables influence what practitioners see as success factors for implementing lean. A survey asked 432 practitioners from 83 factories belonging to two multinational companies for their opinions about what managers should do to ensure the success of the factory-level implementation of lean production. The survey responses were grouped into general success factors, which were then tested for differences across four contingency variables: corporation, factory size, stage of lean implementation and national culture. In general, the analysis supports a generic list of CSFs, but with some minor excep...

Distributed manufacturing: scope, challenges and opportunities

Abstract: This discussion paper aims to set out the key challenges and opportunities emerging from distributed manufacturing (DM). We begin by describing the concept, available definitions and consider its evolution where recent production technology developments (such as additive and continuous production process technologies), digitisation together with infrastructural developments (in terms of IoT and big data) provide new opportunities. To further explore the evolving nature of DM, the authors, each of whom are involved in specific applications of DM research, examine through an expert panel workshop environment emerging DM applications involving new production and supporting infrastructural technologies. This paper presents these generalisable findings on DM challenges and opportunities in terms of products, enabling production technologies and the impact on the wider production and industrial system. Industry structure and location of activities are examined in terms of the democratising impact on participating network actors. The paper concludes with a discussion on the changing nature of manufacturing as a result of DM, from the traditional centralised, large-scale, long lead-time forecast-driven production operations to a new DM paradigm where manufacturing is a decentralised, autonomous near end user-driven activity. A forward research agenda is proposed that considers the impact of DM on the industrial and urban landscape.

New hybrid COPRAS-G MADM Model for improving and selecting suppliers in green supply chain management

Abstract: Greening the supply chain is an increasingly important concern for many business enterprises and a challenge for logistics management. Critical functions within green supply chain management are internal improvements and selection of green suppliers. This study proposes a novel, hybrid model that addresses dependent relationships between various criteria and the vague information coming from decision-makers. The Decision-making Trial and Evaluation Laboratory (DEMATEL) technique structures the relationships among criteria, thereby constructing an influential network relationship map (INRM). Meanwhile the DEMATEL-based, analytical network process (ANP) method aids in obtaining influential weights of the criteria. Decision-makers may hold diverse opinions and preferences due to incomplete information, differences in knowledge or simply conflicts that are inherent between various departments. This can make it difficult to judge the performance of alternatives. One remedy is to apply a modified COmplex PRopor...

A utility-driven approach to supplier evaluation and selection: empirical validation of an integrated solution framework

Abstract: Supplier evaluation and selection (SES) problems have long been studied, leading to the development of a wide range of individual and hybrid models for solving them. However, the lack of widespread diffusion of existing SES models in the industry points to a need for simpler models that can systematically evaluate both qualitative and quantitative attributes of potential suppliers while enhancing the flexibility decision-makers need to account for relevant situational factors. Furthermore, empirical validations of existing models in SES have been few and far between. With a view to addressing these issues, this paper proposes an integrated solution framework that can be used to evaluate both tangible and intangible attributes of potential suppliers. The proposed framework combines three individual methods, namely the fuzzy analytic hierarchy process, fuzzy complex proportional assessment and fuzzy linear programming. The framework is validated through application in a Turkish textile company. The results ...

Supply chain dynamics, control and disruption management

Abstract: This special issue has been inspired by recent tracks and sessions on Supply Network Dynamics, Control and Disruption Management organised at a number of conferences:• 14thIFAC Symposium on Informa...

Dual channel closed-loop supply chain coordination with a reward-driven remanufacturing policy

Abstract: This paper investigates a reward-driven policy, employed in a closed-loop supply chain (CLSC), for acquiring used products earmarked for remanufacture. Under the examined model, a single manufacturer sells products through a retailer as well as directly to end users in a forward supply chain. In the reverse supply chain, three different modes of collection are employed to capture used products for remanufacture: they are through a third party, directly by the manufacturer and from the retailer. Mathematical models for both non-cooperative and centralised scenarios are developed to characterise the pricing decisions and remanufacturing strategies that indicate individual and overall supply chain performance. Optimality of all the proposed models is examined with theory. To coordinate and achieve a win–win outcome for channel members, we proposed a three-way discount mechanism for the manufacturer. Extended numerical investigation provides insights on ways to manage an efficient reward-driven CLSC in a dual...

Proactive environmental strategies and performance: role of green supply chain processes and green product design in the Chinese high-tech industry

Abstract: Though many firms still believe that passive environmental strategies are sufficient, it is pertinent that they move beyond this belief and take a proactive supply chain-wide environmental stance so as to create a sustainable environment. In this paper, we seek to extend current work within green supply chain management by considering multiple green supply chain capabilities and performance measures. We hypothesise the linkage between environmental orientation, green supply chain capabilities and performance by drawing upon stakeholder theory and natural resource-based view. More importantly, our study is the first to distinguish between product and process-related capabilities in the green supply chain area and study their direct and mediating role with respect to environmental and financial performance measures. Using survey data collected from 256 Chinese-based high-tech firms, we analyse several hypothesised relationships. Our results provide strong support for the significant role that green product ...

Developing a resilient supply chain through supplier flexibility and reliability assessment

Abstract: In this study, we examine the optimal allocation of demand across a set of suppliers in a supply chain that is exposed to supply risk and environmental risk. A two-stage mixed-integer programming model is used to develop a flexible sourcing strategy under disruptions. Our model integrates supplier selection and demand allocation with transportation channel selection and provides contingency plans to mitigate the negative impacts of disruptions and minimise total network costs. Finally, a numerical example is presented to illustrate the model and provide insights. The findings suggest that developing contingency plans using flexibility in suppliers’ production capacity is an effective strategy for firms to mitigate the severity of disruptions. We also show that flexibility and reliability of the suppliers and regions play a significant role in determining contingency plans for during disruption. Findings generally show that highly flexible suppliers receive less allocation, and their flexible capacity is r...

Lean manufacturing in Brazilian small and medium enterprises: implementation and effect on performance

Abstract: The main objective of this paper is to investigate the degree to which lean manufacturing (LM) practices are being implemented within Brazilian small and medium enterprises (SMEs), by defining what LM means, in the view of SMEs in Brazil. In addition, the paper investigates the relationship between LM implementation and performance of such companies. The research method used in this paper comprised of an exploratory survey using the partial least-square method with the structural equation modelling technique (PLS-SEM). The results show that the companies studied used practices in a fragmented manner, without a holistic view of LM, which is considered to be one of the most important parts of this approach. Only the constructs of statistical process control, total productive maintenance and employee involvement are being implemented as an integrated approach for Brazilian SMEs. These companies do not take other important constructs such as customer involvement, continuous flow, pull production, set-up time ...

Ergonomics in assembly line balancing based on energy expenditure: a multi-objective model

Abstract: In many assembly systems, ergonomics can have great impact on productivity and human safety. Traditional assembly systems optimisation approaches consider only time and cost variables, while few studies include also ergonomics aspects. In this study, a new multi-objective model for solving assembly line balancing problem is developed and discussed in order to include also the ergonomics aspect. First, based on main features of assembly workstations, the energy expenditure concept is used in order to estimate the ergonomics level, thanks to a new technique, called Predetermined Motion Energy System, which helps rapidly estimate the energy expenditure values. Then, a multi-objective approach, based on four different objective functions, is introduced in order to define the efficient frontiers of optimal solutions. To complete the study, a simple numerical example for a real case is presented to analyse the behaviour of Pareto frontiers varying several parameters linked to the energy and time value.

Understanding big consumer opinion data for market-driven product design

Abstract: Big consumer data provide new opportunities for business administrators to explore the value to fulfil customer requirements (CRs). Generally, they are presented as purchase records, online behaviour, etc. However, distinctive characteristics of big data, Volume, Variety, Velocity and Value or ‘4Vs’, lead to many conventional methods for customer understanding potentially fail to handle such data. A visible research gap with practical significance is to develop a framework to deal with big consumer data for CRs understanding. Accordingly, a research study is conducted to exploit the value of these data in the perspective of product designers. It starts with the identification of product features and sentiment polarities from big consumer opinion data. A Kalman filter method is then employed to forecast the trends of CRs and a Bayesian method is proposed to compare products. The objective is to help designers to understand the changes of CRs and their competitive advantages. Finally, using opinion data in Amazon.com, a case study is presented to illustrate how the proposed techniques are applied. This research is argued to incorporate an interdisciplinary collaboration between computer science and engineering design. It aims to facilitate designers by exploiting valuable information from big consumer data for market-driven product design.

Product recovery optimization in closed-loop supply chain to improve sustainability in manufacturing

Abstract: When business practices shift from a traditional open supply chain to a closed loop instead, the environmental and societal issues are efficiently integrated in business development. However, even an efficiently integrated shift introduces a number of trade-offs due to the contradictory goals that emerge from that business’s economical, environmental and social dimensions. In this paper, we propose a multi-objective mixed integer mathematical problem for a generic closed-loop supply chain (CLSC) network to rationalise how a system’s product recovery helps to improve manufacturing sustainability. The CLSC network proposed in this study consists of a hybrid manufacturing facility, warehouse, distribution centres, collection centres and a hybrid recovery facility (HRF). The proposed model determines the best location for the HRF and optimal flow of products, recovered parts and material in the network while it simultaneously maximises profit, saves activity costs, helps to decrease the harmful effects of the...

Travel time model for double-deep shuttle-based storage and retrieval systems

Abstract: Technological developments in the global supply chain have changed processes in warehousing. This reflects in short response time in handling the orders, which has a consequence on high automation degree in warehousing. An important part of automated warehouses is presented by shuttle-based storage and retrieval systems (SBS/RS), which are used in practice when demand for the throughput capacity is high. In this paper, analytical travel time model for the computation of cycle times for double-deep SBS/RS is presented. The advantage of the double-deep SBS/RS is that fewer aisles are needed, which results in a more efficient use of floor space. The proposed model considers the real operating characteristics of the elevators lifting table and the shuttle carrier with the condition of rearranging blocking totes to the nearest free storage location during the retrieval process of the shuttle carrier. Assuming uniform distributed storage locations and the probability theory, the expressions for the single and d...

Developing environmental and social performance: the role of suppliers’ sustainability and buyer–supplier trust

Abstract: We explore how environmental and social performance of manufacturing firms can be improved as sustainable supply chain management (SSCM) develops and evolves within a firm from internal to external practices. Importantly, this study considers how key suppliers’ sustainability performance and buyer–supplier trust mediate and moderate such a development. A conceptual framework is developed which relies on resource-based theories and emerging empirical evidence. Then, partial least square methodology is applied on survey data from a sample of Italian manufacturing firms. Results show that manufacturing firms’ sustainability performance improves as SSCM develops; however, while internal practices have a direct impact on performance, the effect of external practices on a manufacturing firm’s sustainability performance is fully mediated by key suppliers’ sustainability performance. Yet, buyer–supplier trust significantly influences the scope of such gains. Since evidence suggests that manufacturing firms are st...

Multiple-objective analysis of integrated relief supply and network restoration in humanitarian logistics operations

Abstract: While logistics research recently has placed increased focus on disruption management, few studies have examined the response and recovery phases in post-disaster operations. We present a multiple objective, integrated network optimisation model for making strategic decisions in the supply distribution and network restoration phases of humanitarian logistics operations. Our model provides an equity-based solution for constrained capacity, budget and resource problems in post-disaster logistics management. We conduct designed experiments for this NP-hard problem to analyse important aspects of the integrated problem for both small- and large-sized networks: full vs. partial restoration and pooled vs. separate budgeting approach. Finally, we apply the model to a Hazus-generated regional case study based on an earthquake scenario and generate efficient Pareto frontiers to understand the trade-off between the objectives of interest.

Applying Value Stream Mapping to eliminate waste: a case study of an original equipment manufacturer for the automotive industry

Abstract: Since its beginning, lean manufacturing has built a worldwide reputation based on results related to production improvement and cost reduction in several companies. This management philosophy focuses on customer value creation through the elimination of production wastes. Lean methods and techniques have spread their scope from the automotive industry to a wide range of industries and services. This article presents a case study that describes the use of the lean tool value stream mapping in the production process of automotive parts for a major automotive company. At the beginning of the project, relevant data from the process were collected and analysed. Subsequently, the initial process was mapped, the related wastes were identified, and then future processes were mapped and financial results were estimated. The proposals were presented on kaizen meetings, the action plan was discussed and the decision regarding which option to choose was taken. Consequently, the Cycle Time and the level of the workfor...

An integrated ISM fuzzy MICMAC approach for modelling the supply chain knowledge flow enablers

Abstract: The aim of this study is to identify supply chain knowledge flow enablers (SCKFEs) to inspect interrelationships among these enablers and classify these enablers into driving power and dependence power using an integrated interpretive structural modelling (ISM) and fuzzy Matriced Impacts Croises Multiplication Appliquee a un Classement (MICMAC) methodology. While the ISM methodology analyses the interactions among the SCKFEs, fuzzy MICMAC analysis is employed to obtain insights into the dependencies among the SCKFEs. A total of 34 SCKFEs were identified through the literature review and expert opinion. As an example, an Indian manufacturing organisation is selected that is willing to adopt the successful knowledge flow for improving supply chain (SC) performance to overcome the intense competition among the SC versus SC. The research shows SCKFEs having high driving power and low dependence have strategic importance because of their driving nature, while the SCKFEs having high dependence and low driving p...

A Hierarchical structure of key performance indicators for operation management and continuous improvement in production systems

Abstract: Key performance indicators (KPIs) are critical for manufacturing operation management and continuous improvement (CI). In modern manufacturing systems, KPIs are defined as a set of metrics to reflect operation performance, such as efficiency, throughput, availability, from productivity, quality and maintenance perspectives. Through continuous monitoring and measurement of KPIs, meaningful quantification and identification of different aspects of operation activities can be obtained, which enable and direct CI efforts. A set of 34 KPIs has been introduced in ISO 22400. However, the KPIs in a manufacturing system are not independent, and they may have intrinsic mutual relationships. The goal of this paper is to introduce a multi-level structure for identification and analysis of KPIs and their intrinsic relationships in production systems. Specifically, through such a hierarchical structure, we define and layer KPIs into levels of basic KPIs, comprehensive KPIs and their supporting metrics, and use it to investigate the relationships and dependencies between KPIs. Such a study can provide a useful tool for manufacturing engineers and managers to measure and utilize KPIs for CI.

Structural quantification of the ripple effect in the supply chain

Abstract: In recent years, remarkable advancements have been achieved in quantitative analysis methods for supply chain design (SCD). Typically, cost or service level optimisation has been included in the objective functions. At the same time, supply chain managers face the ripple effect that arises from vulnerability, instability and disruptions in supply chains. This research aimed to quantify the ripple effect in the supply chain from the structural perspective. The research agenda of this study includes issues of integrating operability objectives as new key performance indicators, e.g. resilience, stability, robustness into SCD decisions. The research is based on a simultaneous consideration of both static structural properties of SCD and execution dynamics subject to uncertainty and disruptions. Due to high dimensionality of real SCD problems, such integration can hardly be implemented in only one model. In this study, an original two-model multi-criteria approach is proposed in order to assess the potential ...

Application of interpretive structural modelling and structural equation modelling for analysis of sustainable manufacturing factors in Indian automotive component sector

Abstract: Sustainable manufacturing practices are essential for automotive component manufacturing organisations to ensure competitive advantage. The interrelation between sustainability enablers' namely economic prosperity, environment well-being, social well-being, performance management and research and development need to be analysed for deriving practical insights. Theoretical model development of enablers using interpretive structural modelling (ISM) has been statistically verified using measurement models and structural model of partial least square, structural equation modelling (SEM). In this context, this article presents a combined ISM and SEM approach for building the models with the help of experts for automotive component manufacturing organisation. The measurement and structural model are constructed based on survey among 70 practitioners from automotive component manufacturing organisations in Southern India. The research hypotheses have been formulated to verify the relationship and are analysed. T...

A big data MapReduce framework for fault diagnosis in cloud-based manufacturing

Abstract: This research develops a MapReduce framework for automatic pattern recognition based on fault diagnosis by solving data imbalance problem in a cloud-based manufacturing (CBM). Fault diagnosis in a CBM system significantly contributes to reduce the product testing cost and enhances manufacturing quality. One of the major challenges facing the big data analytics in CBM is handling of data-sets, which are highly imbalanced in nature due to poor classification result when machine learning techniques are applied on such data-sets. The framework proposed in this research uses a hybrid approach to deal with big data-set for smarter decisions. Furthermore, we compare the performance of radial basis function-based Support Vector Machine classifier with standard techniques. Our findings suggest that the most important task in CBM is to predict the effect of data errors on quality due to highly imbalance unstructured data-set. The proposed framework is an original contribution to the body of literature, where our pr...

A knowledge-guided fruit fly optimization algorithm for dual resource constrained flexible job-shop scheduling problem

Abstract: Different from the classical job shop scheduling, the dual-resource constrained flexible job-shop scheduling problem (DRCFJSP) should deal with job sequence, machine assignment and worker assignment all together. In this paper, a knowledge-guided fruit fly optimisation algorithm (KGFOA) with a new encoding scheme is proposed to solve the DRCFJSP with makespan minimisation criterion. In the KGFOA, two types of permutation-based search operators are used to perform the smell-based search for job sequence and resource (machine and worker) assignment, respectively. To enhance the search capability, a knowledge-guided search stage is incorporated into the KGFOA with two new search operators particularly designed for adjusting the operation sequence and the resource assignment, respectively. Due to the combination of the knowledge-guided search and the smell-based search, global exploration and local exploitation can be balanced. Besides, the effect of parameter setting of the KGFOA is investigated and numerica...

Impact of visual performance management systems on the performance management practices of organisations

Abstract: The purpose of this paper was to explore how visual strategy and performance management techniques impact performance measurement and management practices of organisations. A novel visual performance management approach is developed and implemented in qualitative case studies with seven manufacturing SMEs across Europe. The implementation cases demonstrate that visual management systems serve to support ongoing strategy development and implementation, facilitate performance measurement and review, enable people engagement, improve internal and external communication, enhance collaboration and integration, support the development of a continuous improvement culture and foster innovation. Additional explorative and longitudinal research is required to understand the long-term impact of such approaches in both small and larger organisations.

On the risk-averse optimization of service level in a supply chain under disruption risks

Abstract: The worst-case optimization of service level in the presence of supply chain disruption risks is considered for the two different service levels measures: the expected worst-case demand fulfillment rate and the expected worst-case order fulfillment rate. The optimization problem is formulated as a joint selection of suppliers and stochastic scheduling of customer orders under random disruptions of supplies. The suppliers are located in different geographic regions and the supplies are subject to random local and regional disruptions. The obtained combinatorial stochastic optimization problem is formulated as a mixed integer program with conditional service-at-risk as a worst-case service level measure. The risk-averse solutions that optimize the worst-case performance of a supply chain are compared for the two service level measures. In addition, to demonstrate the impact on the cost in the process of optimizing the worst-case service level, a joint optimization of expected cost and conditional service-at...

Barriers to the adoption of green operational practices at Brazilian companies: effects on green and operational performance

Abstract: The objective of this paper is to verify to what degree the internal and external barriers (I/EBs) to environmental management affect the adoption of green operational practices (GOPs) and to determine whether they influence the firms’ operational and green performance in a sample of Brazilian companies. A conceptual framework with 8 hypotheses is proposed and tested at 75 companies using Partial Least Squares-Structural Equation Modeling (PLS-SEM) with WarpPLS 4.0. The main results show that (a) the proposed framework obtained an adequate statistical adjustment, (b) the internal barriers (IBs) are more significant than the EBs when adopting GOPs, (c) GOPs relate directly to the firms’ green and operational performance (OP), (d) the IBs also indirectly influence the firms’ green and OP and (e) the firm size does not significantly influence its green and OP. This work contributes to the literature by showing that companies which are looking for green competitive advantages should try to reduce their IBs. A...

Using game theory for analysing pricing models in closed-loop supply chain from short- and long-term perspectives

Abstract: Closed-loop supply chain (CLSC) management is an environmental approach to supply chain management that aims to prevent hazardous material from entering the nature by means of creating a reverse flow. This paper studies the short- and long-term behaviour of agents in implementing the appropriate collecting strategy in a two-echelon CLSC. In short-term, based on the Stackelberg game, several novel pricing models for different collecting strategies are proposed and compared. Then, the optimal policies of the pricing decisions are determined for each model. The long-term behaviour of companies in implementing collecting process is examined by evolutionary game theory and the most stable strategy is selected. Furthermore, a numerical example is presented to compare the different collecting structures. Finally, a managerial insight is provided to indicate the effect of key parameters such as remanufacturing rate, marketing elasticity and government subsidies on selecting the appropriate strategy.