Modelling an industrial strategy for inventory management in supply chains: The 'Consignment Stock' case

Stock control in Supply Chain management is of concern here, particularly an industrial practice observed in the automotive manufacturing context and defined as 'Consignment Stock' (CS). To understand the potentiality of CS policy, an analytical modelling is offered that refers to the problem of a single-vendor and single-buyer productive situation. A comparison with the optimal solution available in the literature is also shown. The conclusion proposes a method that is useful in identifying those productive situations where CS might be implemented successfully. Results show how CS policy might be a strategic and profitable approach to stock management in uncertain environments, i.e. where delivery lead times or market demand vary over time.     

Hybrid Petri-nets for modelling and performance evaluation of supply chains

Modelling and analysis of complex and co-ordinated supply chains is a crucial task due to its inherent complexity and uncertainty. Therefore, the current research direction is to devise an efficient modelling technique that maps the dynamics of a real life supply chain and assists industrial practitioners in evaluating and comparing their network with other competing networks. Here an effective modelling technique, the hybrid Petri-net, is proposed to efficiently handle the dynamic behaviour of the supply chain. This modelling methodology embeds two enticing features, i.e. cost and batch sizes, in deterministic and stochastic Petri-net for the modelling and performance evaluation of supply chain networks. The model is subsequently used for risk management to investigate the issues of supply chain vulnerability and risk that has become a major research subject in recent years. In the test bed, a simple productive supply chain and an industrial supply chain are modelled with fundamental inventory replenishment policy. Subsequently, its performance is evaluated along with the identification and assessment of risk factors using analytical and simulation techniques respectively. Thus, this paper presents a complete package for industrial practitioners to model, evaluate performance and manage risky events in a supply chain.     

Performance evaluation for tandem multi-factory supply chains: an approximate solution

Predicting the performance of multistage manufacturing systems is usually viewed as challenging because of unexpected machine breakdowns, random processing times, uncertain inter-factory transportation times, etc. In this paper, the authors formulate an approximate model for the tandem manufacturing systems, where the inventory in each buffer is monitored based on the (s, Q) discipline. This model divides a multistage system into a series of primitive line segments, each of which is characterised by a continuous time discrete state Markov process. The model may be applied in two types of systems: (1) tandem flow lines with batch processing and (2) multi-factory manufacturing supply chain, where inter-factory material transportation is required. Based on the model, a number of commonly used performance measures, including throughput, inventory, transportation frequency, etc., can be estimated. These estimates may enable manufacturers to evaluate the performance of the systems, and hence improve the management of production and inventory.     

Location-inventory problem in supply chains: a modelling review

A location-inventory problem (LIP) aims to integrate strategic supply chain design decisions with tactical and operational inventory management decisions. This study provides an extensive review of the existing literature of LIP modelling. A mathematical model is presented for a basic LIP, which can be further developed to incorporate additional features for use in real-world scenarios. We also discuss the evolution of LIP modelling literature over the past three decades and provide summary tables outlining characteristics of the published works including key modelling attributes and objective function cost components. Additional classifications are completed based on the solution methods adopted and real-world applications investigated. Our observations provide important insights and identify potential directions for future research in the field.     

Optimal echelon stock policies for multi-stage supply chains in fuzzy environments

This paper investigates decision-making in multi-echelon serial supply chain management in the presence of imprecision or uncertainty arising from human reasoning, emphasising the computational resolution. The proposed analysis method is based on a combination of the extension principle and the alpha-representation in fuzzy theory and optimisation theory. The problem is first formulated as a fuzzy optimisation model with several fuzzy parameters. To conserve the fuzziness of the input information of the supply chain, such as forecast market demands and inventory costs, a pair of two-level mathematical programs is proposed to identify the lower and upper bounds of the fuzzy performance at different possibility levels, so that the complete membership function can be described. Four example scenarios are solved to demonstrate the validity of the proposed analysis method. The proposed methodology is widely applicable with different types of membership functions for fuzzy parameters, positive lead times or other more complicated cases. The managerial implications are also discussed for reference by decision-makers.     

Assessing the impact of performance determinants in complex MTO/ETO supply chains through an extended hybrid modelling approach

In make-to-order (MTO)/engineer-to-order (ETO) business environments multiple customer-oriented projects compete for and share resources through interdependent engineering and production activities. Deep knowledge of critical dimensions that affect performance is key in this context. For this, we propose a set of determinants – workload, complexity, outsourcing, design reuse, project type, and knowledge/experience with technology, that impact performance. These determinants are input to an extended hybrid simulation model using system dynamics (SD), discrete event simulation (DES) and agent-based simulation (ABS) that tackles the needs imposed by activities of very different nature, as the project development and manufacturing/assembly operations. The hybrid model is applied to the case of an advanced manufacturing company. Through Monte Carlo sampling, the influence of different combinations of determinants in the performance variability is assessed. A correlation analysis shows evidence of association between all performance determinants and the project time and cost, while no evidence of association between the design reuse and project type determinants and the manufacturing and assembly time.     

A multi-objective optimisation approach for order management: incorporating activity-based costing in supply chains

Most of the supply chain order management decision making models proposed in the literature are based mainly on the material flow and capacity constraints without any consideration to the profitability factor. In this paper, we develop a multi-objective mixed-integer programming (MIP) model which considers profitability in order to effectively manage order acceptance decisions in supply chains, subject to capacity constraints by using activity-based costing (ABC). While there are a numbers of decision-making models in literature integrating ABC in supply chains, this study expands the previous models with a more customer-oriented approach. The proposed model fulfils a desirable amount of orders completely and accepts selective number of orders partially with an objective of minimising the amount of residual capacity and increasing the profitability.     

A decision support framework for global supply chain modelling: an assessment of the impact of demand,supply and lead-time uncertainties on performance

We developed a decision support framework for a global manufacturer of specialty chemicals to study the relative impact of demand, supply and lead-time uncertainties on cost and customer service performance. Our approach combines optimisation and simulation methodologies as follows: mathematical models provide optimal plans via a novel approach to the supply chain planning mechanism of the Company. Simulation models execute the supply chain plans so as to allow the examination of the outcomes under the various sources of uncertainty. The iterative use of optimisation and simulation methodologies allows the user the benefit of obtaining optimal solutions while revealing the impact of uncertainties on system performance. Our results indicate that demand uncertainty has the greatest negative impact on performance for the supply chain that we modelled in this study, emphasising the importance of effective forecasting. The relative importance of supply and lead-time uncertainties varies according to the performance measures. While our results are valid for the specific supply chain and the operating environment we modelled, our study emphasises the importance of the ability to model supply chains realistically to obtain valid and useful results.     

Processes and measurement of knowledge management in supply chains: an integrative systematic literature review

During the last 10 years, important contributions about knowledge management (KM) issues in supply chain management (SCM) have been published. The current paper aims to build upon previous literature reviews focused on KM in supply chains (SCs) from an integrative perspective, particularly recognising the studies conducted by Bhosale and Kant (2016. “Metadata Analysis of Knowledge Management in Supply Chain: Investigating the Past and Predicting the Future.” Business Process Management Journal 22 (1): 140–172) and Cerchione and Esposito (2016. “A Systematic Review of Supply Chain Knowledge Management Research: State of the Art and Research Opportunities.” International Journal of Production Economics 182: 276–292) as an effort to discuss the evolution of KM in the SC field. To this end, a systematic literature review including 210 papers is conducted over the period 2008–2017 from three positions previously not addressed jointly within the supply chain (SC) context: research methods employed by the authors; KM processes applied in the business processes across the SC; and intra and inter- organisational performance metrics linked with KM initiatives. Results exhibited that: (i) ‘Survey’ and ‘Case study’ are the two research methodologies mostly employed by authors (ii) the knowledge transfer is discussed in the majority of the studies reviewed, (iii) 114 intra and inter-organisational performance metrics are reported within the SC context from an empirical data approach. Findings concerning previous identified gap analysis and future lines of research are described.     

Dynamic modelling of surge effect and capacity limitation in supply chains

Agile manufacturing has been defined as the capability of reacting to unpredictable market changes in a cost-effective way, simultaneously prospering from the uncertainty. In many industries, vigorously changing markets are demanding more differentiated products in lower volumes and within shorter delivery times. An uncertain environment challenges the response of supply chains. This paper demonstrates, by using a system dynamic simulation, how agility is built into supply chains. Three simulation models are analysed: first, the demand magnification effect in supply chain is studied. Secondly, the analysis is extended to capacity surge effects. Finally, the trade-off between capacity utilization and lead times is discussed. The analysis recommends smaller order sizes, echelon synchronization and capacity analysis as methods of improving the responsiveness of a supply chain. Evidence is provided from simulation runs and established literature. All three models are system dynamics based replications of well-known effects from the research area of production control.     

Model predictive control for inventory management in biomass manufacturing supply chains

This paper presents a centralised model predictive control strategy applied to biomass inventory control in sugarcane industries. Sugarcane industries are important renewable energy producers and an adequate inventory control of their feed material (biomass) can improve energy production. Simple linear discrete-time models with dead-time are developed to predict the controlled variable behaviour. Two layers are used in the controller, in the upper one performance is optimised by an linear programming (LP) algorithm and a multivariable generalised predictive controller (GPC) or multivariable generalised predictive controller with dead-time compensation (DTC-GPC) is used in the lower level. Simulation results in general show that the proposed controllers globally optimise the system behaviour and find an optimal ordering amount for keeping stock levels. In cases of plant/model mismatch DTC-GPC can have a significant and positive impact on the control of stock levels adding one more parameter for achieving minimised oscillatory performances (bullwhip effect).     

Collaboration in humanitarian supply chains: an organisational culture framework

The purpose of this study was to determine the impact that institutional logics and, more specifically, organisational culture can have on humanitarian supply chain (HSC) collaboration. A framework was developed that explicates buyer–supplier collaboration in a humanitarian setting. Twenty-nine semi-structured interviews were conducted with buyers and suppliers. The data indicated that in a HSC, collaborative outcomes, such as new product development, inventory management, and product/service delivery, are influenced by the buyers’ and suppliers’ organisational cultures. Based on suppliers’ characteristics, they can be classified as humanitarian suppliers, commercial suppliers, and humanitarian and commercial suppliers. These groups have distinct organisational cultures. An unexpected finding is that suppliers that serve commercial buyers primarily claim to have encountered no issues in supply chain collaboration with humanitarian buyers, although they have different types of organisational cultures. The factors that lead to successful collaboration are identified as trust, commitment, information sharing and mutual respect. Simultaneously, dominant institutional logics are observed in the dyadic relationship.     

供应链管理中对供方的评价与选择

供应链管理是企业价值链上的重要环节,对供方的选择评价是供应链管理中的一项重要内容。讨论了建立供方评价指标体系应遵循的原则,对供方的评价选择进行了分析,提出了选择评价供方时应注意的几个问题。     

The impact of total quality management on supply chain management and firm's supply performance

This research investigates the relationships among total quality management practices (TQMP), supply chain management practices (SCMP) and firm's supply performance (FSP) in the automotive industry in Thailand. The measurement instruments for SCMP, TQMP and FSP were developed based on an extensive literature review and verified by experts, pilot test and various statistical techniques to ensure reliability and validity in structural equation modeling constructs. The hypothesized model was tested through a path analysis. Qualitative case studies of two large first-tier automotive suppliers were conducted to obtain more in-depth information. We found that the set of SCMP, TQMP and FSP measures are reliable and valid for Thailand's automotive industry. TQMP not only has a significant direct positive impact on SCMP and on FSP but also a significant indirect positive impact on FSP through SCMP.     

A strategic and tactical model for closed-loop supply chains

In this paper, a strategic location-allocation model is developed for the simultaneous design of forward and reverse supply chains. Strategic decisions such as network design are accounted for together with tactical decisions, namely, production, storage and distribution planning. The integration between strategic and tactical decisions is achieved by considering two interconnected time scales: a macro and a micro time. At macro level, the supply chain is designed in order to account for the existing demands and returns, whose satisfaction is planned simultaneously at the micro level where tactical decisions are taken. A Mixed Integer Linear Programming formulation is obtained which is solved to optimality using standard Branch & Bound techniques. Finally, the model accuracy and applicability is illustrated through the resolution of a case study.     

Social and environmental risk management in resilient supply chains: A periodical study by the Grey-Verhulst model

As sustainability and allied concerns are at present gaining greater than before attention amongst stakeholders, enterprises are enforced to consider social and environmental risk assessments along with conventional economic risk assessments. Hence to advance sustainable competitive advantages, the property of resilience is becoming a success factor for enterprises. Resilience is the property of enterprises or their supply chains to resume operations after disruptions and to regain its sustainable competitive advantages quickly and effectively. This study essentially focuses on identifying drivers of social and environmental risk management (SERM) in resilient supply chains and to acknowledge the importance of these drivers towards the implementation of SERM practices of enterprises. Representative case studies of three electronics manufacturing firms were also considered in this research to gain practical insights. Periodical data analysis has been piloted for the collected datasets from these companies. Since the sequences of the collected data show saturated sigmoidal tendencies, the Verhulst model fits best with the data sequences. A Grey-Verhulst model has been implemented in this research and was practically tested for case firms to exemplify the data sequences of prediction and to effectually improve the SERM performances of firms.     

Agile supply chain strategy and supply chain performance: complementary roles of supply chain practices and information systems capability for agility

The paper examines the mediating effect of supply chain (SC) practices on the relationship between agile supply chain (ASC) strategy and SC performance. It further examines the moderating effect of information systems (IS) capability for agility on this mediated relationship. Using the theoretical lenses of complementarity and the information processing view of the supply chain, we hypothesise that strategic supplier partnership, customer relationship, postponement and lean practices, mediate the relationship between ASC strategy and SC performance. We further hypothesise that IS capability for agility moderates each of these mediated relationships. We empirically test the hypotheses using survey data from members of senior and executive management in the logistics/supply chain functions of 205 firms. The paper contributes to the literature on ASCs by theoretically explaining and empirically demonstrating how SC practices and IS capability for agility act together to effect a positive relationship between ASC strategy and supply chain performance.     

A note on supply chain risk classification: discussion and proposal

The main objective of this note is to complement the excellent work on supply chain risk classification by Rangel et al. [International Journal of Production Research, vol. 52 (7), 2014]. In this note, we consider the use of ISO/IEC (International Organisation for Standardisation/International Electrotechnical Commission) norms to support the supply chain risk classification. Its purpose is to develop, maintain and promote standards in the fields of information technology and information communications technology. Therefore, to improve on the work by Rangel et al. (2014), ISO 27036 (Information Security for Supplier Relationship) and ISO 28000 (Specification for Security Management Systems for the Supply Chain) are aligned with ISO 31000 (Risk Management–Risk Assessment Techniques). Furthermore, since supply chain risk management does not have a standardised process, these norms, particularly ISO 31000, can serve as a guide to improve its implementation.     

Sustainable supply chains for supply chain sustainability: impact of sustainability efforts on supply chain risk

Supply chain managers across the globe are finding it difficult to manage the increasingly complex supply chains despite adopting a variety of risk mitigation strategies. Firms on the other hand have also been adopting various kinds of environmental and social sustainability practices in recent times to reduce carbon footprint and improve their image on the social front. However, very few studies in the extant literature have examined the impact of sustainability practices on supply chain risk. We address this important gap in literature by empirically testing this relationship, using primary data from six manufacturing sectors and 21 different countries including developed as well as emerging markets across the globe. Our findings indicate that risk mitigation strategies do not always reduce the actual supply chain risk experienced by firms, whereas sustainability efforts help reduce supply chain risk, especially in emerging market contexts. In addition, we find that, while reactive risk mitigation strategies on their own fail to reduce supply chain risk, they are effective when used in conjunction with sustainability efforts. We also find that preventive risk mitigation efforts are only effective in mature supply chains such as the OECD countries.     

Modelling of outsourcing decisions in global supply chains. An empirical study on supplier management performance with different outsourcing strategies

Outsourcing decisions in global supply chains are critical to a business’ competitiveness. This study investigates and compares the supplier management in Taiwanese enterprises under different outsourcing strategies. Base on an empirical study through questionnaires, we investigate the supplier management and critical success factors of the Taiwanese enterprises. It is shown that different outsourcing strategies should be deployed by different types of industries, and a good working relationship with suppliers and customers are paramount to success. The important issues related to supplier management include supplier capability to deliver on time, long term contract strategy with suppliers, supplier evaluation, and quality of material from suppliers.