Henk Zijm

Reconfigurable layout problem

This paper addresses the reconfigurable layout problem, which differs from traditional, robust and dynamic layout problems mainly in two aspects: first, it assumes that production data are available only for the current and upcoming production period. Second, it considers queuing performance measures such as work in progress inventory and product lead time in the objective function of the layout problem. A process to solve the reconfigurable layout problem is proposed. A previously developed, open queuing network-based analytical model, called Manufacturing system Performance Analyser, is used to estimate the stochastic performance measures of a layout. These are combined with deterministic performance measures such as material handling cost to determine the layout for the next period. A case study is used to illustrate the process of solving the reconfigurable layout problem.

On multi-stage production/inventory systems under stochastic demand

This paper was presented at the 1992 Conference of the International Society of Inventory Research in Budapest, as a tribute to professor Andrew C. Clark for his inspiring work on multi-echelon inventory models both in theory and practice. It reviews and extends the work of the authors on periodic review serial and convergent multi-echelon systems under stochastic stationary demand. In particular, we highlight the structure of echelon cost functions which play a central role in the derivation of the decomposition results and the optimality of base stock policies. The resulting optimal base stock policy is then compared with an MRP system in terms of cost effectiveness, given a predefined target customer service level. Another extension concerns an at first glance rather different problem; it is shown that the problem of setting safety leadtimes in a multi-stage production-to-order system with stochastic lead times leads to similar decomposition structures as those derived for multi-stage inventory systems. Finally, a discussion on possible extensions to capacitated models, models with uncertainty in both demand and production lead time as well as models with an aborescent structure concludes the paper.

Logistics and Supply Chain Innovation: Bridging the Gap between Theory and Practice

This contributed volume presents state-of-the-art advances in logistics theory in various fields as well as case studies. The book reports on a number of recently conducted studies in the Dinalog and the Effizienz Cluster Logistik Ruhr, thus bridging the gap between different perspectives of theoretical and applied research. A selection of theoretical topics, practical examples, case studies and project reports is presented in this volume. The editors carefully selected contributions from a wide variety of projects, which were carried out in both the Dinalog cluster and the Effizienzcluster Logistik Ruhr. The contributions are grouped in five main sections, each representing key domains in the evolution of logistics and supply chain management: sustainability, urban logistics, value chain management, IT-based innovation, knowledge management. This book is intended for both researchers and practitioners in the field of logistics and supply chain management, to serve as an important source of information for further research as well as to stimulate further innovation.

Two-level manufacturing system performance analyser

Open queuing network is a commonly used analytical tool for modelling manufacturing systems. Parametric decomposition is a proven solution method for analysing open queuing networks and can estimate key performance measures such as work-in-process inventory, cycle time, and machine utilisation, fairly accurately. This paper presents a two-level hierarchical open queuing network model, which considers numerous features seen in a real manufacturing system including, machine set-up, material handling device setup (for example, loading and unloading operations), process as well as transfer batching, empty travel of the material handling device and machine or material handling device failures. The model first analyses a higher level open queuing network whose nodes are aggregations of a set of machines. The higher level network is solved via the parametric decomposition method and the results are then disaggregated to get lower level, e.g. machine specific, results. The motivation, algorithm and its relationship with the one-level model are discussed. Experimental results are provided to show that the two-level model provides comparable results with the one-level model in addition to its computational and managerial advantages. In addition, both are shown to provide better results than a recent method available in the literature that is based on the well-known queuing network analyser.

Logistics and Supply Chain Management: Developments and Trends

The demand for sustainable logistic and supply chain processes poses enormous challenges in terms of technology integration, the development of new business models, cultural change and job qualification, and as such requires a real paradigm shift. In this paper, we start with a brief sketch of how modern logistics and supply chains emerged as a result of diversification and specialization of industrial production, globally scattered availability of resources and more demanding consumer markets. Jointly with advances in freight transport and communication technologies, these developments have led to the global economy we face today. The strong growth of trade and consumption however also revealed some essential weaknesses of the system that renders current practices in the long run unsustainable—in social, environmental and economic terms (people, planet, profit). Future supply chains should no longer deplete scarce natural resources or contribute to climate change, should avoid environmental pollution and withstand safety and security threats, while at the same time remaining competitive and satisfying high labor quality standards. This requires not only the application of advanced technologies to mitigate or even neutralize these negative effects, but also the development of smart business models, new job qualification standards and corresponding (lifelong) training and education programs at all levels, including artificial intelligence based learning.

Economic sustainability of biogas production from animal manure: a regional circular economy model

Purpose This paper aims to understand the implementation of a circular economic business where animal manure is used to produce biogas and alternative fertilizer in a regional network of manure suppliers and biogas producers and to reveal the impacts of five variables (manure quantity, transportation distance, manure dry content, manure price and manure discharge price) on the economic sustainability of manure-based biogas supply chains. Design/methodology/approach An enterprise input-output approach is used to model physical and monetary flows of the manure-based biogas supply chain. Computational experiments are performed on all variables to identify under which conditions the cooperation is beneficial for all actors. Findings The cooperation is profitable for a large-scale farm (>20,000 t/year) if biogas producer (b) pays farmer (f) to receive its manure (5 €/t) or if f sells manure for free and manure disposal costs are >10 €/t. Cooperation is always profitable for b if f pays b to supply its manure (5€/t). If b receives manure for free, benefits are always positive if b is a medium-large-scale plant (>20,000 t/year). For a small-scale plant, benefits are positive if manure dry content (MDC) is ≥12 per cent and transportation distance is ≤10 km. Originality/value The paper adds value to the biogas production research, as it makes holistic analysis of five variables which might change under different policy and geographical conditions. The investors in biogas production, suppliers and transportation companies can find correspondence to empirical findings for their own site-specific cases.

Maintenance Service Logistics

Capital goods, such as manufacturing equipment, trains, and industrial printers, are used in the primary processes of their users. Their availability is of key importance. To achieve high availability, maintenance is required throughout their long life cycles. Many different resources such as spare parts, service engineers and tools, are necessary to perform maintenance. In some cases, e.g. for trains, also maintenance facilities are required. Maintenance service logistics encompasses all processes that ensure that the resources required for maintenance are at the right place at the right time. In a broader sense, it also includes maintenance planning and design-for-maintenance. We first discuss capital goods and the requirements that their users have, which leads us to basic maintenance principles and the structure of typical service supply chains. Next, various relevant decisions and supporting theories and models are discussed. Finally, we discuss the latest developments within maintenance service logistics.

Stochastic Inventory Models

We discuss inventory systems in an independent demand setting, where demand over time is modeled as a stationary stochastic process. We begin with some basic notions and definitions on inventory management, followed by a discussion of well-known (and applied) control systems. Under periodic review and a linear cost structure, it is known that the optimal control policy has a critical level structure, hence we analyze such critical level policies in detail. After that, in an advanced section, we turn to multi-echelon or multi-stage systems. We present a complete analysis of the decomposition result proven initially by Clark and Scarf, and its analogue in distribution systems, i.e., systems with an arborescent instead of a linear structure (state-of-the-art). Computational aspects are briefly discussed after which we close with some guidelines for further reading.

Objectives, Educational Developments and Structure of the Book

Operations, logistics, and supply chains are essential enablers in a modern economy. At the same time, operational, logistics, and supply chain systems are changing fundamentally as a result of technological and societal developments, requiring both researchers as well as skilled professionals to rethink them and to incorporate new functionalities. This in turn poses new demands on the way vocational and academic learning, as well as on-the-job training programs for operations, logistics, and supply chain management are designed. This book is an attempt to serve students, researchers, and business practitioners by providing information and background material at various levels. In this introductory chapter, we discuss the scope and structure of the book. Reading this chapter is recommended to determine how to use the book in classroom lectures and seminars, gather background information or for studying specific topics. In each chapter, suggestions for further reading and resources for the growth of lateral and critical thinking are provided in order to spread the learning curve—sometimes even slightly beyond the operations, logistics, and supply chain management domain. Readers are encouraged to explore the additional material for their own development and to build general learning and research capacities.

Operations, Logistics and Supply Chain Management: Definitions and Objectives

Operations, logistics and supply chains are catalysts in any modern economy and therefore essential contributors to economic prosperity and societal welfare. This chapter briefly sketches the origins of the field and presents a case study on the importance of a balanced logistical organization from the 17th century, after which formal definitions and objectives are introduced. In addition, we discuss relations with other management areas as well as with other science domains such as law or social and political sciences. Topics and concepts in this chapter are discussed at an elementary level, aiming to provide an introduction to the topical field of operations, logistics, and supply chain management.