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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. ...

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...

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.

In the past 10 years, ubiquitous manufacturing (UM) has received a growing amount of attention among researchers in the manufacturing community because ubiquitous computing technologies (UCTs) can be applied to address a wide range of issues in the manufacturing industry, e.g. manufacturing processes and equipment, manufacturing management and planning. However, to the best of the authors’ knowledge, there is a lack of comprehensive and critical review from a holistic view of the state-of-the-art UM and its systems. This paper aims to provide a concise overview of the technical features, characteristics and broad range of applications of UM systems published between 1997 and 2017. Among these selected articles, more than 70% of them were published between 2012 and 2017, and they are considered as recent pertinent works which will be discussed in detail. The unique aspects of this paper lie in that this paper summarises and analyses a broad range of the state-of-the-art implementation of UM systems from a ...

This paper proposes a scheduling strategy for irregular curved blocks to address the complex spatiotemporal coupling scheduling problem related to the entered time, the entered sequence, the setting positions and the rotated angles for the curved blocks in a shipbuilding yard. The strategy presents a makespan-based curved blocks – classification and selection rule to fulfil the programming time for the entry of the curved blocks into the workplace and realises the suppression on the delay. Useless stepping search of curved blocks in occupied workplace is avoided by combining the lowest centre-of-gravity rule with the calculation method of the remained workplace proposed in this paper. A modified genetic ant colony algorithm was proposed, which apply the ease to premature characteristics of GA and the excellent local optimisation ability of ACO, to let and promote the algorithm falls into local optimum. Then the large-scale and full-range mutation will be implemented to make the algorithm jump out of the original local optimisation to search more local optimal solutions so that the global optimal solution can be achieved. Finally, a software system for algorithm verification was developed which conducts the comparative analysis of the algorithms and verifies the validity of the algorithm proposed.

This paper presents an assessment method to measure the lean transformation (LT) stage of an LT enterprise. Although there are many assessment tools to measure the various aspects of lean practices in enterprises, there is none to measure the stage of LT using the enterprise transformation characteristics from enterprise level. In this paper, the characteristic metrics and characteristic model of LT cycle were extracted from the basic capacity, process power and transformation results. Then, an assessment approach based on fuzzy nearness degree and TOPSIS is proposed to determine the stage of LT. Finally, an example is shown to highlight the procedure of the proposed method. This paper shows that the proposed model is very well suited as an assessment tool for enterprises in the manufacturing industry and other industries to evaluate the LT stage.

Pre-existing knowledge buried in manufacturing enterprises can be reused to help decision-makers develop good judgements to make decisions about the problems in new product development, which in turn speeds up and improves the quality of product innovation. This paper presents a graph-based approach to knowledge reuse for supporting knowledge-driven decision-making in new product development. The paper first illustrates the iterative process of knowledge-driven decision-making in new product development. Then, a novel framework is proposed to facilitate this process, where knowledge maps and knowledge navigation are involved. Here, OWL ontologies are employed to construct knowledge maps, which appropriately capture and organise knowledge resources generated at various stages of product lifecycle; the Personalised PageRank algorithm is used to perform knowledge navigation, which finds the most relevant knowledge in knowledge maps for a given problem in new product development. Finally, the feasibility and ...

Managing production systems where production rates change over time due to learning and forgetting effects poses a major challenge to researchers and practitioners alike. This task becomes especially difficult if learning and forgetting effects interact across different stages in multi-stage production systems as rigid production management rules are unable to capture the dynamic character of constantly changing production rates. In a comprehensive simulation study, this paper first investigates to which extent typical key performance indicators (KPIs), such as the number of setups, in-process inventory, or cycle time, are affected by learning and forgetting effects in serial multi-stage production systems. The paper then analyses which parameters of such production systems are the main drivers of these KPIs when learning and forgetting occur. Lastly, it evaluates how flexible production control based on Goldratt’s Optimised Production Technology can maximise the benefits learning offers in such systems. ...

Manufacturing companies are increasingly shifting their value proposition from a product-centric perspective to Product-Service-System (PSS). This evolution allows companies to improve the customisation of their offer and to contribute to reduce material flows and consumption, thus enhancing sustainability. However, when companies introduce PSS offers, they have to face higher complexity and dynamism, as customer behaviours, process requirements and sustainability assessment must be considered during the design and the development of the new solutions. In this paper, after the identification of the main PSS dynamic features, the authors argue that business process simulation (BPS) could represent an effective tool to cope with the dynamics and the complexity entailed in a sustainable PSS. This paper analyses and compares existing BPS approaches identifying the hybrid simulation (HS) modelling as a promising approach. In fact, according to the critical PSS features, HS allows grasping PSS features and inte...

More and more industrial products have begun to adopt iterative design modes. Opinions collected from all sides in each round of iterations are used as bases to make products that are able to capture the changes of customer demand dynamically and to respond to these changes in a timely manner. In this context, it becomes important for product designers and manufacturers to study the evolution of opinions as well as the product scheme along with design iteration to determine its regularity. This paper integrates the Hegselmann–Krause model into product improvement process, and develops a dynamic model from the view of opinion dynamics. The dynamic model simultaneously converges the evolution of customers’ opinions, professional designers’ opinions and the product scheme. The paper also analyses the interaction mechanism among different opinions as well as the mechanism between opinions and the product scheme. The experimental results determine that the product scheme, customers’ opinions and professional d...

Over the last few years, the fourth industrial revolution has attracted more and more attentions all around the world. In the current literature, there is still a lack of efforts to systematically review the state of the art of this new industrial revolution wave. The aim of this study is to address this gap by investigating the academic progresses in Industry 4.0. A systematic literature review was carried out to analyse the academic articles within the Industry 4.0 topic that were published online until the end of June 2016. In this paper, the obtained results from both the general data analysis of included papers (e.g. relevant journals, their subject areas and categories, conferences, keywords) and the specific data analysis corresponding to four research sub-questions are illustrated and discussed. These results not only summarise the current research activities (e.g. main research directions, applied standards, employed software and hardware), but also indicate existing deficiencies and potential re...

To date, research has mainly discussed the definition and classification of producer services. Yet many companies require an integrated solution of products and producer services. The aim of this paper is to propose a model of the ecological evolution of manufacturing service systems (MSS) driven by service providers. This model adopts modular thinking to integrate dispersive producer services into an entire MSS, the process of which forms the ecological evolution of MSS. This paper applies ecological theory to build the ecological evolution mechanism of MSS. In this mechanism, the predator–prey relationship is used as a metaphor for the relationships between manufacturers and service providers in a MSS. A predator–prey model is built to simulate the ecological evolution of MSS. A predation cellular genetic algorithm is adopted to optimise this evolution. The proposed model and algorithm are demonstrated and validated by a case study of MSS in bicycle industry. This study contributes to theory by proposin...

The Physical Internet (PI) logistics system is an innovative logistics concept that has been gathering a lot of attention lately. This system consists of open, modular and shared containers and transit hubs to move goods globally. The purpose of this paper is to compare the performance of PI with regard to the conventional (CO) logistics system in order to quantify the advantages and disadvantages of PI from a truck and driver routing perspective with an explicit constraint on maximum return time for drivers. The comparison presented in this work is carried out through Monte-Carlo simulation within a sequential three-phase optimisation framework. Based on our analysis, PI reduces driving distance (and time), GHG (greenhouse gas) emissions and the social cost of truck driving. On the other hand, it increases the number of container transfers within the PI logistics centres. This insight is a contribution of the paper and reinforces the current literature on PI. The other main contribution of the paper is a...

Manufacturing companies are striving hard to remain competitive hence, they rely on a number of resources to meet customers’ expectations, among which cutting tools are included. This paper addresses the problems faced in the management of cutting tools activities. Production managers have highlighted the lack of procedures containing metrics and targets that would show them whether their company is able to perform an efficient management, and if it is capable of supporting the deployment process. In this context, this paper presents a novel lean environmental benchmarking (LEB) method for performing a diagnosis of practices and performances to support the implementation of a cutting tool management strategy and/or the effective management of these assets. Strategic, technical and logistical aspects are addressed, particularly, with regard to management focused on lean manufacturing and environmental aspects. Field studies were performed in nine Brazilian companies in the metal-mechanical sector to valida...

This paper investigates the multiskilled worker training and assignment (MWT&A) problem of the seru production system (SPS), which is a new type of assembly line configured as multiple assembly cells, or so-called serus. The configuration of the SPS emphasises production efficiency and flexibility, achieved by multiskilled workers (MWs) able to cope with the demand of high-variety and low-volume manufacturing. Well-arranged and trained MWs are viewed as a critical factor when it comes to enhancing the performance of SPSs. This paper studies the MWT&A problem in the SPS with the aim of minimising the total cost, specifically, the workers’ training cost and the balance cost of processing times of the MWs in serus. This study provides an applicable mathematical programming model and designs a two-phase heuristic, named the SAIG algorithm, to effectively and efficiently solve this problem. The performance of the proposed algorithm is demonstrated by a comparison with the state-of-the-art heuristic through a s...

This paper considers the zone automated order fulfilment systems with a number of zones linked by a main conveyor. Each zone has a number of dispensers and a buffer. Each dispenser holds one type of item and dispenses the items for an order into a buffer before the items are merged to the main conveyor. Due to variability of the mix of item types and number of items for each type in successive orders, idle time or open space on the conveyor can occur if the buffers merge the items to the conveyor sequentially. The idle time prolongs the order fulfilment duration. This paper aims to provide a solution to reduce the idle time or open space by optimising the merging sequences among zones. A model is developed to find merging sequences with minimum order fulfilment time. However, the model is strongly NP-hard. A greedy heuristic-based solution approach is thus developed. Experiment performance shows that the presented solution can reduce the order fulfilment time approximately 5% with both empirical data and ...

Network structures have been diffusely adopted in logistics systems, where the most critical target is completing the delivery within the promised timeframe. This paper focuses on a single commodity in a multistate intermodal logistics network (MILN) with transit stations and routes to involve three parameters: a route’s capacity, delivery time and time window. There is a carrier along each route whose number of available containers is multistate because the containers can be occupied by other customers. The delivery time consisting of the service time, travel time and waiting time varies with the number of containers and vehicle type. The arrival time at the transit station should be within the time window, the interval between the earliest and latest acceptable arrival times. This paper evaluates the system reliability, the probability that the MILN can successfully deliver sufficient amount of the commodity to meet market demand via several transit stations under the delivery time threshold and time wi...

The ever-growing awareness of environmental protection has significantly influenced the method of manufacturing products. Due to the introduction of new processes, the management of sustainable manufacturing shows different characteristics to those of traditional systems. Sustainable manufacturing systems have attracted a great deal of attention in the past 20 years as an emerging manufacturing approach. Particularly in the last 10 years, the number of papers focusing on the topic of sustainable manufacturing systems’ management has increased rapidly. More and more practical factors have been considered and integrated into this area which makes it more complex, but closer to reality. This paper aims to classify the mathematical problems dealing with the management of sustainable manufacturing systems. More than 100 related papers mainly from 1994 to 2015 have been selected and reviewed and divided into three categories according to the main elements in a manufacturing system: production planning and contr...

Capacitated lot-sizing and scheduling problem under disruption environment is a frequently encountered problem in manufacturing industry. This paper focuses on dealing with the case that the disruption is caused by machine breakdowns. Such case frequently arises during the process of the execution of a planned schedule. As a result, a reschedule needs to be applied, and then the decision-maker naturally may compare the reschedule results with the original one. Rather than from the conventional cost-saving perspective, this paper makes comparison from the attitude or the human behaviour perception of decision-makers towards the deviation from the original schedule. A non-linear mixed integer programming model is constructed with the objective of minimising the negative deviation based on the Prospect Theory, a psychologically more accurate description of decision-making. The non-linear term introduced by the Prospect Theory is approximately linearised by a series of piecewise linear segments. Then, an MIP-...

A specialised case of the classical one-dimensional cutting stock problem (1D-CSP) with six main additional features is adapted in this paper to model and solve planning unit operations with limited resources in the make-to-order industrial environment, generating a new decision-making problem. The objective is to satisfy demand using the minimum number of manufacturing cycles. Although there is a large number of applications, this paper proposes a decision model directed at the vulcanising operation during the manufacturing of rubber curved hoses in the automotive industry. Because each vulcanising cycle (VC) uses a considerable amount of resources, the need to minimise the total number of VCs is of importance due to its direct relationship with lead time and productivity. An integer-programming model based on a network optimisation formulation is proposed to solve the problem to optimality and allows for construction of the mathematical model. In addition, due to the limited capacity of computers to sol...

This paper proposes a stochastic linear mixed-integer programming model for integrated decisions in the preparedness and response stages in pre- and post-disaster operations, respectively. We develop a model for integrated decisions that considers three key areas of emergency logistics: facility and stock prepositioning, evacuation planning and relief vehicle planning. To develop a framework for effective relief operations, we consider not only a cost-based but also an equity-based solution approach in our multiple objectives model. Then a normalised weighted sum method is used to parameterise our multiple objective programming model. This paper suggests a compromise between the cost, and the equity of relief victims. The experiments also demonstrate how time restrictions and the availability of relief vehicles impact the two objective functions.

In order to differentiate from competitors in terms of customer service, warehouses accept late orders while providing delivery in a quick and timely way. This trend leads to a reduced time to pick an order. This paper introduces workload forecasting in a warehouse context, in particular a zone picking warehouse. Improved workforce planning can contribute to an effective and efficient order picking process. Most order picking publications treat demand as known in advance. As warehouses accept late orders, the assumption of a constant given demand is questioned in this paper. The objective of this study is to present time series forecasting models that perform well in a zone picking warehouse. A real-life case study demonstrates the value of applying time series forecasting models to forecast the daily number of order lines. The forecast of order lines, along with order pickers’ productivity, can be used by warehouse supervisors to determine the daily required number of order pickers, as well as the allocation of order pickers across warehouse zones. Time series are applied on an aggregated level, as well as on a disaggregated zone level. Both bottom-up and top-down approaches are evaluated in order to find the best-performing forecasting method This work was supported by the IWT Agency for Innovation by Science and Technology.

Although having structural system models which determine system behaviours is critical to plan, control and manage many complex systems (e.g. manufacturing and production systems), we often do not have pre-defined structural system models. We need to perform reverse engineering which is to collect and mine observable system data in order to discover structural system models. This paper presents a reverse engineering algorithm that can be used to discover a causal system model which is one kind of structural system model and represents causal relations of system factors. In a causal relation, the presence of one system factor causes the presence of another system factor. The paper also shows the computational complexity of the algorithm. The paper presents the application and performance of the reverse engineering algorithms to data in two application fields.

Design for Manufacturing (DFM), especially the use of manufacturing knowledge to support design decisions, has received attention in the academic domain. However, industry practice has not been studied enough to provide solutions that are mature for industry. The current state of the art for DFM is often rule-based functionality within Computer-Aided Design (CAD) systems that enforce specific design requirements. That rule-based functionality may or may not dynamically affect geometry definition. And, if rule-based functionality exists in the CAD system, it is typically a customization on a case-by-case basis. Manufacturing knowledge is a phrase with vast meanings, which may include knowledge on the effects of material properties decisions, machine and process capabilities, or understanding the unintended consequences of design decisions on manufacturing. One of the DFM questions to answer is how can manufacturing knowledge, depending on its definition, be used earlier in the product lifecycle to enable a more collaborative development environment? This paper will discuss the results of a workshop on manufacturing knowledge that highlights several research questions needing more study. This paper proposes recommendations for investigating the relationship of manufacturing knowledge with shape, behavior, and context characteristics of product to produce a better understanding of what knowledge is most important. In addition, the proposal includes recommendations for investigating the system-level barriers to reusing manufacturing knowledge and how model-based manufacturing may ease the burden of knowledge sharing. Lastly, the proposal addresses the direction of future research for holistic solutions of using manufacturing knowledge earlier in the product lifecycle.

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 ...

Recent research and development in production industry reveals a movement to cyber-physical production systems and Internet of things enabled manufacturing. In this context, ways in which enterprise processes are conceptualised and executed are changing. Decentralising production by applying interlinked cyber-physical production resources breaks up the traditional boundaries between different process abstraction layers. Heterogeneous smart devices and processes at all levels in the industrial control need to interact in such systems. In this paper, requirements from the field of Business Process Management towards the vertical integration of business and production processes are derived. With respect to the identified requirements the eligibility of the Subject-oriented Process Management (S-BPM) approach for vertical process integration is depicted. At the core, the paper investigates the applicability of S-BPM to achieve vertical process integration and reports lessons learnt from two industrial applica...

In cellular manufacturing systems (CMSs), an operator plays an important role. Because operators work for long-time periods in a production area, an increase in job satisfaction and system productivity occurs if the consistency of operators’ personal characteristics are considered in the design of CMSs. In a CMS, a cell formation problem (CFP) focuses on grouping and allocating machines, part families and operators to manufacturing cells. This paper considers a decision-making style (DMS) as an operator’s personal characteristic index in a CFP for designing a psychologically consistent CMS. DMS influences not only the interaction between two operators, but also the work that operator does on a machine. Hence, this paper develops a novel multi-objective mathematical model for the CFP considering consistency between each two operators in each cell and consistency between operator and his/her assigned machine(s). Because of possibility of a change in the primary DMS of a person to the backup one, this paper ...

The management of a military supply chain (SC) involves the integration of production, packaging, warehousing, repair, maintenance and transportation of army supplies. In this paper, we focus on the integrated demand-responsive scheduling of maintenance and transportation operations within the SC. We consider a modular representation of a SC, in which the maintenance and transportation operations constitute the corresponding modules. An efficient integration of these operations is carried out by an additional controlling (commanding) module. We describe and analyse the optimisation problems arising in each module. The main contribution of the paper is that the analysis and optimisation of the controlling module permit to enhance the performance of the entire SC. Computational experiments prove the validity and effectiveness of the suggested models.

There is a need for identifying computing power hours and storage utilisation along with total cost optimisation. The present paper focuses on optimal selection of application loading process on the cloud services considering relevant factors. Using this model, small companies that plan to develop applications and use cloud services may determine cost and optimal selection of service by taking into account its own as well as provider’s perspectives into consideration. The paper consists of four stages. First stage deals with the estimation of required computing power hours in the planned duration. Second stage relates to the calculation of storage capacity. Third stage corresponds to the formation of multi objective goal programme to prioritise computing power hours and storage utilisation requirements of applications and optimise total cost of usage. Finally, fourth stage deals with the mixed integer non-linear programming to minimise total cost considering other variable factors. For small application d...

The study examines how the utilisation of a new performance measurement system (PMS) influences supply chain management (SCM) and what kind of impacts the new system has on the performance of the supply chain. The paper utilises a longitudinal research setting where the data was gathered in two semi-structured interview studies after an action research project in which a new measurement system was designed and developed. The findings show how a PMS serves as a catalyst of inter-organisational knowledge transfer and promotes shared learning. The results also show how knowledge transfer and shared learning led to improved performance of the supply chain. The paper contributes by opening up the practical mechanisms through which performance measurement provides value for SCM and by showing how inter-organisational transfer of performance information catalyses learning and performance improvement. The paper looks beyond the design of performance measures and provides a view on the practice of supply chain per...

There is a strong need for recovery decision-making for end-of-life (EOL) products to satisfy sustainable manufacturing requirements. This paper develops and tests a profit maximisation model by simultaneously integrating recovery option selection and disassembly planning. The proposed model considers the quality of EOL components. This paper utilises an integrated method of multi-target reverse recursion and partial topological sorting to generate a feasible EOL solution that also reduces the complexity of genetic constraints handling. In order to determine recovery options, disassembly level and disassembly sequence simultaneously, this paper develops an improved co-evolutionary algorithm (ICA) to search for an optimal EOL solution. The proposed algorithm adopts the evolutionary mechanism of localised interaction and endosymbiotic competition. Further, an advanced local search operator is introduced to improve convergence performance, and a global disturbance strategy is also suggested to prevent premat...

In this paper, we are concerned with the problem of the ‘helicopters and vehicles’ intermodal transportation of medical supplies in response to large-scale disasters. To deal with the disadvantages of the use of classic Fuzzy C-Means (FCM) in the intermodal transportation optimization, two balanced FCM methods, i.e. FCM with capacity constraints and FCM with number constraints, are formulated to select emergency distribution centers (EDCs) and assign medical aid points, which could construct balanced ‘helicopters and vehicles’ intermodal transportation network. Then, considering helicopter travel time, transfer time and vehicle delivery time, a clustering-based intermodal routes optimization model is presented to produce intermodal transportation routes. Numerical experiments are presented to show the effectiveness and advantage of the developed approach, and observe the impact of number of EDCs and transfer efficiency at EDCs on the performance of intermodal transportation. This paper could provide metho...

This paper studies an integrated control strategy of production and maintenance for a machining system which produces a single type of product to meet the constant demand. Different from previous research, we assume in this study that during the production, the production rate not only influences the life of cutting tool, but also the reliability of the machine. Both the replacement of cutting tool and the preventive maintenance (PM) of machine are considered in this paper. The machine is preventively maintained at the Nth tool replacement or correctively repaired at the machine failure, whichever occurs first. PM and corrective repair may cause shortage which can be reduced by controlling inventory. There are two decision variables p and N, where p denotes the production rate and N denotes the number of cutting tool replacement before the PM is performed. An integrated model is developed to simultaneously determine the optimal production rate and PM policy that minimise the total expected cost per unit i...

Given a reward structure, this paper addresses an optimal replacement problem for complex multi-component systems. To maintain revenue stream resulting from system, the system is inspected according to a homogeneous Poisson process and certain actions are carried out in response to the system state. Decisions are based on a performance measure described by a Squared Bessel process. Given some assumption, we explore the inherent relation between the Squared Bessel process and an extended Gamma (EG) process. Since there are some flow of income and increasing costs due to inspections, the problem is to optimally stop processing the system and carrying out a renewal to maximize the reward functional. To this end, using the local characteristics of the EG process as a stopping criterion and the expected total discounted reward as a measure of policy, this paper aims at determining an optimal operating (stopping) time which truly balances both income and cost and so maximizes the expected discounted reward over...

Due to the repetitive nature of inventory planning over the planning horizon, the operator in charge has to perform planning tasks repetitively, and consequently s/he becomes more familiar with the tasks over time. Familiarity with the tasks suggests that learning takes place in inventory planning. Even though the operator’s learning over time might improve his/her efficiency, prior research on fuzzy lot-sizing problems mostly overlooked the effect of human learning in their models and its impact on the operator’s performance. To close the research gap in this area, this paper models the operator's learning in a fuzzy economic order quantity model with backorders. The paper models a situation where the operator applies the acquired knowledge over the cycles in setting the fuzzy parameters at the beginning of every planning cycle, where his/her learning ability includes the cognitive and motor capabilities of a human being. Subsequently, a mathematical model which takes account of a two-stage human learnin...

Independent Component Analysis (ICA) has been extensively used for detecting faults in industrial processes. While applying ICA to process monitoring, the inability of identifying the important components affect the fault diagnosis ability. For further improving the competence of ICA, this paper proposes an approach integrating ICA, Durbin Watson (DW) criterion and Support Vector Data Description (SVDD) to monitor non-Gaussian process for detecting faults. In the proposed approach, namely ICA–DW–SVDD, ICA is a non-Gaussian information extractor from original variables, DW identifies dominating ICs, and SVDD plays the role of fault detector. This paper also discusses the retracing method to detect original variables causing disturbance in the process. One simulation case and the Tennessee Eastman Process are used to demonstrate the effectiveness of our proposed approach.

The question this special issue would like to address is how to harvest big data to help decision-makers to deliver better fact-based decisions aimed at improving performance or to create better strategy? This special issue focuses on the big data applications in supporting operations decisions, including advanced research on decision models and tools for the digital economy. Responds to this special issue was great and we have included many high-quality papers. We are pleased to present 13 of the best papers. The techniques presented include data mining, simulation and expert system with applications span across online reviews, food retail chain to e-health.

Natural resources industries, such as the forest product industry, must deal with variable input material, which affects their efficiency and their ability to accurately predict output yields. In order to address this, the industry can use technologies that adapt to variable input, or plan its operations taking variability into account. In the Canadian softwood lumber industry, the first approach is used with the adoption of advanced technologies that adapt sawing patterns to logs’ and work-in-process characteristic using scanners technology. Another approach to deal with material variability is input material classification. Specific characteristics can be measured to classify input material and reduce variability within each class. However, whether the process involves logs, mining ores or recycled papers, material classification has both a value and a cost. This paper first proposes a method based on classification tree analysis to classify hardwood logs. Next, using agent-based simulation, it analyses...

This article introduces the relationship between complexities and proactive management practices in supply chain resilience, particularly due to global sourcing (GS) strategies. The main objectives of this paper are as follows: (i) explain the various aspects of GS rather than reporting the trends and implications described in the literature, (ii) view GS in terms of complexity theory and (iii) investigate the resilience of supply chain due to GS complexity and suggest strategies to overcome complexities. We propose a GS resilience framework for future researchers to analyse the impact of GS complexity factors on supply chain resilience with respect to three outcomes: (i) risk and innovation, (ii) benefit in terms of sales promotion and (iii) challenges and responsiveness. Based on the framework, this introductory article summarises the papers appear in this special issue. This article would be useful to researchers and practitioners to further explore the role of complexities, proactive management strategies on GS resilience.

This paper proposes an automated scanning process of a structured light system for objects without overhangs. The processes for scanning those objects need to plan scanning directions that minimise the missing area on a three-dimensional surface during the scanning process. Thus, the processes require an approach that finds the next scanning direction efficiently in terms of computational costs. This paper develops a scanning simulation approach to meet this requirement. In order to apply the developed approach, the proposed process generates a solution space for candidate-scanning directions, and represents an intermediate 3D model. The developed approach traverses the solution space in a virtual environment and executes virtual scanning for the intermediate 3D model. The virtual scanning result of each candidate-scanning direction is analysed in order to evaluate the contribution for filling missing area. The proposed process defines key scanning directions in the solution space through the iterative ex...

This paper presents a new multivariate process capability index (MPCI) which is based on the principal component analysis (PCA) and is dependent on a parameter which can take on any real number. This MPCI generalises some existing multivariate indices based on PCA proposed by several authors when or . One of the key contributions of this paper is to show that there is a direct correspondence between this MPCI and process yield for a unique value of . This result is used to establish a relationship between the capability status of the process and to show that under some mild conditions, the estimators of this MPCI is consistent and converge to a normal distribution. This is then applied to perform tests of statistical hypotheses and in determining sample sizes. Several numerical examples are presented with the objective of illustrating the procedures and demonstrating how they can be applied to determine the viability and capacity of different manufacturing processes.

In this paper, the concept of cost-tolerance functions based on data directly obtained from the manufacturing process is proposed. Traditional models used in manufacturing field define cost-tolerance relationships from mathematical functions whose relationship with the process is not usually set in a clear way. In this work, proposed models allow to obtain cost-tolerance functions directly from parameters measured on manufacturing process. The paper defines some of these functions using statistical distributions derived from the population of manufactured parts. A general methodology to reach a cost-tolerance function from any distribution of the manufactured parts is proposed. Once functions are defined, an application example is presented. Finally, the main criteria for suitable appropriateness use of models are established.

In this paper, the extended Resource Renting Problem (RRP/extended) is presented. The RRP/extended is a time-constrained project scheduling problem, in which the total project cost is minimised. In the RRP/extended, this total project cost is determined by a number of extra costs, which are defined in this paper. These costs are based on the costs that are used in the traditional Resource Renting Problem and the Total Adjustment Cost Problem. Therefore, the RRP/extended represents a union of these two problems. To solve the RRP/extended, a scatter search is developed. The building blocks of this scatter search are specifically designed for the RRP/extended. We introduce two crossovers and an improvement method. The efficiency of these building blocks will be shown in the paper. Furthermore, a sensitivity analysis is presented in which the five costs have diverse values.