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Transforming Pulp and Paper (P&P) mills into Integrated Forest Biorefineries (IFBR) is a prominent solution to save Canadian P&P industry that has been facing decline of conventional paper demand. ...

The pulp and paper industry has significant sustainability implications and necessarily requires a careful consideration of direct and lower-tier suppliers for effective sustainable supply chain ma...

International audience; An intertwined supply network (ISN) is an entirety of interconnected supply chains (SC) which, in their integrity secure the provision of society and markets with goods and services. The ISNs are open systems with structural dynamics since the firms may exhibit multiple behaviors by changing the buyer-supplier roles in interconnected or even competing SCs. From the positions of resilience, the ISNs as a whole provide services to society (e.g., food service, mobility service or communication service) which are required to ensure a long-term survival. The analysis of survivability at the level of ISN requires a consideration at a large scale as resilience of individual SCs. The recent example of coronavirus COVID-19 outbreak clearly shows the necessity of this new perspective. Our study introduces a new angle in SC resilience research when a resistance to extraordinary disruptions needs to be considered at the scale of viability. We elaborate on the integrity of the ISN and viability. The contribution of our position study lies in a conceptualization of a novel decision-making environment of ISN viability. We illustrate the viability formation through a dynamic game-theoretic modelling of a biological system that resembles the ISN. We discuss some future research areas.

This paper introduces the background, concept and definition of the Industry Commons. It initiates a discussion on the positioning of the Industry Commons Ecosystem (ICE) with respect to current research directions in advanced manufacturing and production systems that shape advances in engineering and technology, novel business models and innovation breakthroughs. The potential value of data sharing across industrial domains is estimated at over $100 billion, particularly in view of optimising manufacturing processes. Data sharing across domains however faces a series of well-documented challenges associated with the lack of semantic interoperability and related standards, management of trust and sustainability. Solving bottlenecks in data sharing requires a systemic approach to data management, which can account for all aspects of data use, levels of application, attribution and dynamic exchanges. In this paper we propose a high-level ecosystem approach that integrates societal values with digital affordances of industry's cognitive-assisted processes, remote interfacing, hybrid applications and large-scale value networks. Early development of an Ontology Commons EcoSystem (OCES) is presented as the key enabling framework for Industry Commons interoperability and a series of enabling frameworks form the basis of future research directions in Trusted Data Sharing and Closed-Loop Lifecycle Management for greater sustainability.

This study examines a two-stage two-dimensional cutting stock problem encountered by a paper mill company. The problem includes various machine-related and operational constraints based on real-world situations. Paper products are manufactured using two major cutting processes. Each cutting machine has a specific minimum and maximum width for input and output rolls and is limited by the maximum number of rolls it can cut at the same time. A mathematical model is presented to formally address the problem and an efficient multiple-choice knapsack-based heuristic algorithm is proposed to solve the problem. To demonstrate the efficiency of the proposed heuristic algorithm, computational experiments are conducted on test data-set generated from real-world data provided by a large paper mill company in the Republic of Korea.

This paper offers a review of the development and use of multi-agent modelling techniques and simulations in the context of manufacturing systems and supply chain management (SCM). The objective of the paper is twofold. First, it presents a comprehensive literature review of current multi-agent systems (MAS) research applications in the field of manufacturing systems and SCM. Second, it aims to identify and evaluate some key issues involved in using MAS methods to model and simulate manufacturing systems. A variety of different MAS applications are reviewed in three different classified research areas: production design and development, production planning and control, and SCM. In presenting a detailed taxonomy of MAS applications, the paper describes MAS application domains from five different perspectives. The review suggests the MAS approach represents a feasible framework for designing and analysing real-time manufacturing operations, since the approach is capable of modelling different levels of agen...

The privatisation of the Iran newsprint industry has caused an increase in production and decrease in importation. Recognition of effective criteria in newsprint privatisation will accelerate privatisation of the industry. The goal of the research is expediting privatisation in the Iran newsprint industry through benefits, costs, opportunities and risk merits. We applied analytical hierarchy process (AHP) to solve the problem plus questionnaires and pair wise comparisons of the matrices by the experts have also been done in the research. The results show a decrease of budget deficiency, national debts (economic and financial), limiting rules, heavy taxes (economic and executive), encouragement possibility, absorption of foreign, internal investment (economic and financial) and limiting regulative costs (economic and financial) which are the most important sub criteria regarding benefits, costs, opportunities and risks merits, respectively.

In this paper, we present an algorithm that solves a paper reel layout problem where the available space is divided into equal-size cells. The problem is to find a layout with the minimum transport...

To enable you to remain competitive in future, you must already start to focus your company on the task of meeting the challenges that are emerging from development trends stretching back over several years and which are becoming more apparent all the time. These trends are leading to increasing levels of complexity, dynamism and uncertainty in the corporate environment. This paper is an attempt to highlight these technological and structural developments, frequently referred to as megatrends: changes of a fundamental nature with far-reaching implications for the economy and society with attendant opportunities and threats to industry. One focal point of this paper will therefore be the fundamental developments in the microelectronics sector and their wider implications, which will necessarily lead to a consideration of the technologies of IT and telecommunications. Another aspect receiving attention here will be the problems facing industry in the wake of structural change of this magnitude as well as th...

This special issue consists of selected papers from the 3rd International Conference on Manufacturing Research (IMRC2005) held at Cranfield University on 6th – 8th September 2005, in the theme of enabling technologies and frameworks for new product development. The papers have been updated, extended and further peer reviewed and improved to the high standard of the journal. Initially 12 papers (around 10% of the total papers presented at the conference) were requested for extension and further review, and 9 papers are finally selected for inclusion in this special issue.

In this paper we present some of the recent advances in the quality and reliability engineering methodologies. These advances include change point detection, monitoring processes with correlated observations, monitoring and control of multivariate processes, integration of the statistical process control with engineering process control, accelerated life testing, degradation models, predictive maintenance, and software reliability engineering. Future directions of research in quality and reliability engineering and their challenges are also discussed.

This paper deals with the problem in designing an efficient production system where perishable raw materials are to be professed into several kinds of end-products. This model can clarify the relationship between the production capacity and the buffer inventory of end-products that are able to control, within their acceptable limits, both the decaying loss of harvested raw materials and the out-of-stock level of end-products.

The technological evolution which contributed to the early development of integrated computerized manufacturing systems (ICOMS) is presented and the significance and characteristics of U.S.A. manufacturing are illustrated. The human aspects in the design and use of manufacturing systems are outlined. Some solutions to human issues in ICOMS are mentioned.

In the material flow sector, there is a great potential for rationalization which should be taken advantage of. In this report, modular elements for automated material flow in manufacturing— particularly in flexible manufacturing cells and systems—are presented and explained in the form of concepts for systems. The technical design and the implementation of these material flow components are illustrated on the basis of flexible manufacturing systems already built or in the planning stage.

As an aid in evaluating efforts to reduce process downtime rates and to facilitate resource allocation decisions, a model of the downtime severity rate and statistical methods for estimating and evaluating two or more downtime severity rates are presented. Time down or cost per downtime incident is assumed to follow a gamma distribution. An expression for a one-sided upper statistical tolerance limit on the downtime severity rate is derived. Examples of statistical analysis using data from a paper manufacturing facility are provided.

The paper is baaed on two interlinked concepts, demonstrated by three investigations, one in England, two in Canada. When faced with the necessity to rank in order of priority a series of decisions which must be made within a finite range of choice, the ranking when arranged cumulatively by priority follows a definite pattern which can be expressed by the relationship y = axb, which is illustrated graphically as a straight line plot on log-log graph paper. In all three enquiries; one concerns the purchase of women's shoeB, one with the sorting out of the priorities within the problems of a religious organization, the third with ranking the decisions that are taken by industrial executives, in the equation y =y axb has a value of between 0·4 and 0·6. The similarity is striking. It is felt that it is only possible to discover the genuine ranking of priorities within a finite range by allowing the person concerned, man or woman, complete freedom of choice. In Case 1 there was the physical ranking i...

International audience; The boom in online sales has inspired the enthusiasm of manufacturers to include their own online sale channel with the retailer’s offline channel. This paper investigates the impact of consumer transfer in a capital-constraint dual-channel supply chain and examines the optimal operational decision by considering a Stackelberg game. We capture the trade credit coordination mechanism of the supply chain facing with stochastic demand. The results show that trade credit contract would alleviate financial pressure of the capital-constraint retailer and achieve coordination in the dual-channel supply chain. Besides, the adoption of trade credit stimulates the ordering behaviour of retailers. However, by using trade credit, the default risk increases for the capital-constraint retailer compared to the retailer with sufficient capital. The manufacturer shares the risk with the retailer by trade credit in dual-channel supply chain. Furthermore, the effects of consumer transfer rates on the setting of the trade credit parameters are also presented in this paper.

The Vehicle Routing Problem (VRP) is one of the most intensively studied combinatorial optimisation problems for which numerous models and algorithms have been proposed. To tackle the complexities, uncertainties and dynamics involved in real-world VRP applications, Machine Learning (ML) methods have been used in combination with analytical approaches to enhance problem formulations and algorithmic performance across different problem solving scenarios. However, the relevant papers are scattered in several traditional research fields with very different, sometimes confusing, terminologies. This paper presents a first, comprehensive review of hybrid methods that combine analytical techniques with ML tools in addressing VRP problems. Specifically, we review the emerging research streams on ML-assisted VRP modelling and ML-assisted VRP optimisation. We conclude that ML can be beneficial in enhancing VRP modelling, and improving the performance of algorithms for both online and offline VRP optimisations. Finally, challenges and future opportunities of VRP research are discussed., Submitted to International Journal of Production Research

It is widely recognised that performance measurement systems (PMS) are important for the management of a factory, business enterprise or public sector organisation. However, the case can be made that the development of PMS and organisational forms are inextricably linked. As the economic, technical and trading environment evolves, organisations need to adapt, and so do the measurement and management systems. In this editorial, we will retrace the history of PMS from early factory costing systems through to the multi-dimensional approaches widely used today. As the world evolves, organisations and PMS need to evolve too with the papers in this special issue reflecting this. These papers lead us to reconsider the future of PMS as climate change, the internet of things (IoT) and new technology drive us forward towards a complex and uncertain future.

International audience; This paper investigates the impacts of preferential credit policy, faced by capital constraint retailers, on coordinating the supply chain. Apart from different bank’s and manufacturer’s risk preferences, preferential credit is also affected by the retailers’ exogenous collateral. We establish the preferential credit coordinating model (PCCM) to examine the optimal decisions and coordinate the supply chain with different financing channels, such as the preferential bank loan, preferential trade credit and portfolio credit. In this paper, we conclude some critical findings. Firstly, we find that the retailer’s optimal would improve its optimal order quantity in the coordinated supply chain when he finances from a risk-pursuing bank or the manufacturer. Secondly, the retailer’s financial cost would be shared with the manufacturer whether the retailer utilises preferential trade credit or bank financing channel. Thirdly, the capital constraint retailer would prefer preferential trade credit to the other financing methods for the purpose that the preferential trade credit could improve the coordinated supply chain’s efficiency. Finally, we capture different impacts of collateral and risk preference on the supply chain. This article supplements the existing literature on supply chain finance with a preferential credit insight into the condition of the coordinated supply chain.

Supply chain finance (SCF) as a crucial approach plays a key role in improving commitment, trust, financial flows, and profitability in a supply chain (SC). Many industrial organisations finance their SC through two resources: internal financing (buyer) and external financing (bank). The main objective of this paper is to develop an advanced data envelopment analysis (DEA) model for measuring the sustainability of financing resources of Industry 4.0 technologies. To do so, for the first time a non-radial DEA model in the presence of both zero inputs and ratio data is proposed. In this paper, the sustainability factors, including economic, environmental, and social factors are incorporated into the proposed approach. The developed DEA model, for the first time, is applied in SCF. The results show the most sustainable financial resource for investing in Industry 4.0 technologies. Also, the inputs and outputs’ inefficiencies are determined.

Artificial lighting is a constant companion in everyday private and working life, influencing visibility in interior spaces as well as outdoors. In recent years, new technical solutions have extended traditional lighting systems to become ‘smart’. Different types of smart lighting systems are available on the market today, and researchers have concentrated on analysing their usability and efficiency, especially for private households, office buildings and public streets. This paper presents a systematic literature review to analyse the state-of-knowledge of technologies and applications for smart lighting systems. The results of the review show that smart lighting systems have been frequently discussed in the literature, but that their potentials in industrial environments, such as production and logistics, has rarely been addressed in the literature so far. Lighting systems for industrial environments often have very different requirements depending on the working environment and operating conditions. Based on the results of the literature review, this paper contributes to closing this research gap by discussing the usage potential of smart lighting systems to improve the efficiency of warehouse order picking, which is an application that may benefit from various functions smart lighting systems provide. Several propositions are developed that emphasise research opportunities and managerial implications in this context.

Kitting is a materials-feeding principle commonly used with mixed-model assembly, but literature is lacking with respect to how kit quality can be supported. The purpose of this paper is to create an understanding of the links between kit preparation design aspects and kit preparation error types, that can be useful to support kit quality. The paper draws on empirical data from a multiple case study in the automotive industry to study how typical kit errors are linked to eight kit preparation design aspects: location, work organisation, storage policy, batching policy, storage packaging, kit carrier and container, picking information system, and error communication. The findings suggest several opportunities related to kit preparation design aspects for preventing kit errors and facilitating kit error corrections. The paper extends earlier knowledge and can support kit quality of industrial kit preparation.

International audience; This paper provides a systematic review and analysis of the game-theroy-based research in Green Supply Chains Management (GSCM). Based on a rigorous content analysis of 108 papers carefully selected from the literature, we present a detailed picture of the current state of this research and point to the promising future directions. Our analysis shows a rapid increase in the number of publications during the last three years, with an imbalance in the contribution of the publishing outlets, as nearly two third of the reviewed papers are published by only four journals. Results also show the dominance of deterministic static models and simple two-level SC structures. Developing stochastic models, considering the risk and the evolutionary nature that inherently characterise the business environment and investigating more complex multi-level SC structures are among the promising future research opportunities.