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The workload control literature highlights the importance of balancing the shop floor workload, but also acknowledges that this can conflict with processing the most urgent orders – hence, there is a trade-off. In practice, shops contain many complexities, e.g. simultaneous batching and sequence-dependent set-up times that may conflict with processing the most urgent orders and require other solutions than workload balancing to avoid capacity losses. This adds to the trade-off dilemma, which traditionally only considers timing and balancing. This paper develops a framework that determines whether to address a complexity through order release or dispatching. It comprises two dimensions: (i) the typical position of a complexity in the routing of an order and (ii) the criticality of the complexity. A case study is presented, which demonstrates the framework’s utility and illustrates the development of specific solutions designed to handle the complexities. Most complexities present in the case require handling at the order release stage. The challenges of handling multiple complexities at this decision level are evaluated. Finally, the implications for managers and future research are outlined. [ABSTRACT FROM PUBLISHER]

This paper focuses onto a situation arising in most real-life manufacturing environments when scheduling has to be performed periodically. In such a scenario, different scheduling policies can be adopted, being perhaps the most common to assume that, once a set of jobs has been scheduled, their schedule cannot be modified (‘frozen’ schedule). This implies that, when the next set of jobs is to be scheduled, the resources may not be fully available. Another option is assuming that the schedule of the previously scheduled jobs can be modified as long as it does not violate their due date, which has been already possibly committed to the customer. This policy leads to a so-called multi-agent scheduling problem. The goal of this paper is to discern when each policy is more suitable for the case of a permutation flowshop with common due dates. To do so, we carry out an extensive computational study in a test bed specifically designed to control the main factors affecting the policies, so we analyse the solution space of the underlying scheduling problems. The results indicate that, when the due date of the committed jobs is tight, the multi-agent approach does not pay off in view of the difficulty of finding feasible solutions. Moreover, in such cases, the policy of ‘freezing’ the schedule of the jobs leads to a very simple scheduling problem with many good/acceptable solutions. In contrast, when the due date has a medium/high slack, the multi-agent approach is substantially better. Nevertheless, in this latter case, in order to perceive the full advantage of this policy, powerful solution procedures have to be designed, as the structure of the solution space of the latter problem makes extremely hard to find optimal/good solutions. [ABSTRACT FROM PUBLISHER]

Abstract, Aiming at the regenerative chatter problem which restricted the machining efficiency in the milling of thin-walled parts, an adjustable workpiece holder for machining thin-walled parts was proposed based on series mode coupling. Firstly, the adjustable workpiece fixture model was designed based on the principle of series mode coupling, and two new optimal tuning strategies (amplitude tuning and negative real part tuning) were proposed to improve the dynamic stiffness and milling stability of the fixture. Secondly, self-adaptive mechanisms such as rotating spring and eddy current module were used to realize the coupling between fixture mode and part mode, and conductive plate was introduced for damping adjustment. The feasibility and effectiveness of the workpiece fixture were verified by the part milling test with clear mode. The results indicate that the fixture is feasible and effective, the cutting surface roughness decreases from Ra 2.4 µm to Ra 0.9 um when the cutting depth is 3 mm. Compared with the conventional holder, the dynamic stiffness and milling stability of the proposed holder is significantly improved. [ABSTRACT FROM AUTHOR]

‘Robustness’ is an important concept used in quality engineering for the improvement of quality in a manufacturing process. A process which is insensitive to noise variation is called a robust process. The robustness is modelled by several researchers and practioners for its design and implementation in a manufacturing process. A review of all these approaches is essential in order to assess their strengths, limitations and applicability under different process conditions and constraints. Over the years, many of these approaches have found widespread application in measuring, assessing and modelling of process robustness in manufacturing and other industries. In this paper, an attempt has been made to review critically the existing approaches as proposed and applied for measuring and evaluating robustness of manufacturing processes. Based on the critical appraisal, the key issues are identified and a generic framework for modelling and measuring of process robustness in single- and multi-stage manufacturing processes is presented. [ABSTRACT FROM PUBLISHER]

Research into moderators, which support collaborative teams by proactively making team members aware of actions or potential problems which may affect them, began in the 1990s, in the context of supporting collaborations during concurrent engineering projects. This paper provides a background to the evolution of moderators and explores their role in supporting virtual organisations. A collaboration moderator (CM) is an evolution of earlier moderators and is capable of behaving differently for different types of users and therefore caters for the varying requirements of individual users depending on the roles they have in the collaborations. This paper describes the architecture and components of a CM from an implementation perspective. Prototype CMs have been developed during the EU-funded SYNERGY project, and two use cases for which the prototype CMs were implemented as a service (a Pre-Creation use case and an Operational use case) are also discussed in this paper. [ABSTRACT FROM AUTHOR]

The response time variability problem (RTVP) is a scheduling problem that has a wide range of real-world applications in mixed-model assembly lines, multi-threaded computer systems, machine maintenance, waste collection and others. The RTVP arises whenever products, clients or jobs need to be sequenced in such a way that the variability in the time between the points at which they receive the necessary resources is minimised. The RTVP has been demonstrated to be NP-hard and heuristic and metaheuristic techniques are needed to solve large, real-life instances. The best results, on average, in the literature for the RTVP were obtained with variable neighbourhood search hybidised with multi-start. Several algorithms based on simulated annealing are proposed to solve the RTVP. An extensive computational experiment is carried out and it is shown that the solution of the RTVP is clearly improved. [ABSTRACT FROM PUBLISHER]

Fixtures are used to fixate, position and support workpieces and represent a crucial tool in manufacturing. Their performance determines the result of the whole manufacturing process of a product. There is a vast amount of research done on automatic fixture layout synthesis and optimisation and fixture design verification. Most of this work considers fixture mechanics to be static and the fixture elements to be passive. However, a new generation of fixtures has emerged that has actuated fixture elements for active control of the part–fixture system during manufacturing operations to increase the end product quality. This paper analyses the latest studies in the field of active fixture design and its relationship with flexible and reconfigurable fixturing systems. First, a brief introduction is given on the importance of research of fixturing systems. Secondly, the basics of workholding and fixture design are visited, after which the state-of-the-art in active fixturing and related concepts is presented. Fourthly, part–fixture dynamics and design strategies which take these into account are discussed. Fifthly, the control strategies used in active fixturing systems are examined. Finally, some final conclusions and prospective future research directions are presented. [ABSTRACT FROM PUBLISHER]

This paper examines the crude oil procurement practices of Chinese oil refineries to suggest improved procurement policies that can reduce the cost associated with fluctuating oil prices in the international spot market. In the industrial environment, the purchase price of crude oil is based on the spot price at the time of delivery rather than that at the time of ordering. Therefore, the purpose of this paper is to develop a procurement model that factors in the spot prices at both the time of ordering and the time of delivery so that the total procurement cost can be minimised over the planning horizon. First, the shortcomings of the current procurement policy of a typical Chinese refinery are presented. A model to address these shortcomings is then developed and embellished by incorporating market information dynamics through Bayesian learning. The effectiveness of the proposed models is compared with the current practice using the historical spot price data of crude oil from two representative spot markets; this comparison verifies that the model with Bayesian sampling performs well empirically and can result in considerable cost savings. [ABSTRACT FROM AUTHOR]

We study the optimal selling price of a deteriorating product under a deterministic situation in a finite time horizon where the time horizon is either known or unknown. Inventory holding cost is expressed as a quadratic function of the current inventory level. Given a known time horizon, we develop a model by considering the deterioration dynamics of the product, and show its equivalence to a generalised optimal control problem of a linear quadratic form, i.e. an optimal dynamic tracking problem with constraints on the control variable. An optimal pricing policy is derived based on the maximum value principle. The control policy takes a state feedback form; it exhibits a closed-loop relationship between the optimal selling price (control variable) and the optimal inventory level (state variable). Given an unknown time horizon, an optimal pricing policy is derived through a similar approach when the initial inventory level meets certain conditions. Numerical situations are conducted to illustrate the effectiveness of the derived price control policies. Some interesting managerial insights are discussed. [ABSTRACT FROM PUBLISHER]

We study the scheduling problem of minimising weighted completion times on parallel identical batching machines with dynamic job arrivals and incompatible job families. Each job is associated with a family, weight (priority), release time, and size. Batching machines can process simultaneously up to a specified total size of the jobs of a particular family. The scheduling problem can be represented by. We present a mathematical model and heuristic algorithms employing different local search procedures individually and sequentially under a variable neighbourhood search scheme. We have shown that among local searches, repositioning the batches instead of jobs yields better results. The best-performing heuristic algorithm is capable of generating solutions within 0.6% of the best overall heuristic solution for each instance in a reasonable amount of time. When this heuristic is compared against the mathematical model, solutions that are 3.7% above optimal on average in the 15-job problem instances are possible. [ABSTRACT FROM PUBLISHER]

With the urgency of remanufacturing and environmental concerns, closed-loop supply chain (CLSC) networks have drawn the attention of researchers. Although there are many CLSC network models in the literature, most of them do not consider uncertainty in general terms. However, practical situations are often not well defined and thus cannot be described precisely in real world CLSCs. In this paper a mixed integer fuzzy mathematical model is proposed for a CLSC network which includes both forward and reverse flows with multiple periods and multiple parts. A fuzzy multi-objective model (FMOM) approach is applied to take into account the fuzziness in the capacity, objectives, demand constraints and also in the reverse rates. Computational results are presented for a number of scenarios to show and validate applicability and flexibility of the model. Results show that the proposed model presents a systematic framework which enables the logistics manager (LM) to adjust the search direction during the solution procedure to obtain a desired satisfactory solution. [ABSTRACT FROM PUBLISHER]

In a batch manufacturing process a cross-correlation exists among dimension deviations of different parts. The modelling and control of these deviations are essential to improve product dimension quality. Traditional dimension deviation statistical control methods have been focused on retrospectively analysing part dimension feature, while based on the spatial relationship between part dimensional features and error sources showed in part dimension error propagation model, this paper presents a method to control part dimension deviation in batch manufacturing that focuses on error sources. At each operation, total part deviation is separated into three components corresponding to three error sources. Therefore, a multivariate exponentially weighted moving average (MEWMA) chart for error sources is proposed to control part dimension deviations with identified error sources attribute to part dimension deviation. Efficiency and reliability of this model were verified by simulation analysis in common error source abnormal patterns, and the model is proved to be effective for detecting small deviations in a batch manufacturing process. [ABSTRACT FROM PUBLISHER]

In order to stimulate innovation during the collaborative process of new product and production development, especially to avoid duplicating existing techniques or infringing upon others’ patents and intellectual property rights, the collaborative team of research and development, and patent engineers must accurately identify relevant patent knowledge in a timely manner. This research develops a novel knowledge management approach using ontology-based artificial neural network (ANN) algorithm to automatically classify and search knowledge documents stored in huge online patent corpuses. This research focuses on developing a smart and semantic oriented classification and search from the sources of the most critical and well-structured knowledge publications, i.e. patents, to gain valuable and practical references for the collaborative networks of technology-centric product and production development teams. The research uses the domain ontology schema created using Protégé and derives the semantic concept probabilities of key phrases that frequently occur in domain relevant patent documents. Then, by combining the term frequencies and the concept probabilities of key phrases as the ANN inputs, the method shows significant improvement in classification accuracy. In addition, this research provides an advanced semantic-oriented search algorithm to accurately identify related patent documents in the patent knowledge base. The case demonstration analyses 343 chemical mechanical polishing and 150 radio-frequency identification patents sample sets to verify and measure the performance of the proposed approach. The results are compared with the previous automatic classification methods demonstrating much improved outcomes. [ABSTRACT FROM PUBLISHER]

This study considers a two-echelon system in which a vendor produces a product at a finite production rate and supplies it to several buyers facing independent normally-distributed demands. The product is delivered to the buyers using a set of different speed vehicles with identical capacity and different operating costs. The issues of lead time reduction and the service level constraint on the buyers have been incorporated in the model. A model is formulated to determine the optimal production–inventory policy, vehicle routes and vehicle type for each route by minimising the related production, inventory, lead time crashing and transportation costs of the system while satisfying the service level constraint on each buyer. A coordinated two-phase iterative approach is proposed to solve the model. Finally, a numerical example is included to describe the solution approach and illustrate the results. [ABSTRACT FROM PUBLISHER]

In order to gain a competitive advantage in the globalised environment, a company has to operate with a high level of agility in terms of responding quickly and flexibly to changes in competitive criteria, the market, and customer demands. Agility has become an important strategic factor in competition. When the design stage of an original equipment manufacturer (OEM)'s or original design manufacturer (ODM)'s product is completed, and it starts to enter the mass production stage, a number of uncertain factors are often encountered, which may delay the manufacturing process and lead to lost business opportunities. Focusing on this issue, the present research establishes a hybrid approach to discovering the critical agility factors when launching a new product into mass production. In this research, interpretive structure modelling (ISM) is first utilised to identify the interactive causal relationships of the employed agility factors. Further, an analytical network process (ANP) model is applied to obtain the importance weights of the agility criteria based on the dependence or feedback relationships among the factors obtained from the results of ISM. As a result, both a visualised causal relationship and a quantified representation of the critical agility criteria can be provided to aid managers in effective decision-making. [ABSTRACT FROM AUTHOR]

We develop a system dynamics model to examine the cumulative effects of continuous improvement programmes for repair and setup times on the cycle time of a simple single-stage production system. The relationship between system performance and repair and setup times is captured using the Factory Physics approach. We find that modest rates of improvement in multiple areas in parallel yield cumulative benefits over time comparable with those obtained by a large reduction in a single parameter, especially when there is significant uncertainty in the degree of improvement that can be obtained, or in the degree to which improvements can be sustained over time. These results provide an insight into the success of the Toyota Production System and related lean manufacturing approaches where continuous improvement is an ongoing activity across the work environment. [ABSTRACT FROM AUTHOR]

Today's industry faces new challenges such as diverse customer demands, shorter product development cycles and cost pressure, which compel manufacturing firms to change their production paradigm from one-size-fits-all mass production toward mass customisation. Over the past decades, modular design has received great attention as a key enabler for mass customisation, and component sharing and platform modularity have been quite popular strategies for modular design. While modular design approaches and their strategies offer a number of advantages such as late product differentiation and changeability, there are unfortunately negative aspects, for example, sales loss due to reduced performance compared to integral design approaches, which have received little attention. Therefore, we propose a hybrid model of the two strategies in order to develop the most profitable product family. A detailed numerical analysis provides empirical support for the feasibility and effectiveness of the hybrid model. [ABSTRACT FROM AUTHOR]

This paper reports evidence from a survey, aimed at testing whether and how Information and Communication Technologies (ICTs), which enable the adoption of product-service systems, can contribute to value creation. This analysis builds on previous contributions, according to which companies that are enriching their product offering through value-added services (the so-called servitisation strategy) often report lower levels of profitability, owing to the poor performance of their operating process. A wide stream of research claims that companies that invest in ICTs can enjoy valuable outcomes, since the adoption of such technologies results in processes that are more efficient and more responsive. Our hypothesis concerns the possibility of leveraging ICTs at operating process level so as to pursue a servitisation strategy. The in-field analysis presented in this paper concerns a sample of 109 companies located in Italy; data collected through the survey have been analysed using the structural equation modelling approach. The evidence presented demonstrates that ICTs can have a relevant impact on value creation because they lead to superior responsiveness of operating processes and to sound improvements in the product offering. In particular, companies that are able to embed such superior responsiveness into their product offering can further boost value creation. [ABSTRACT FROM AUTHOR]

This paper considers the problem of production planning of unreliable batch processing manufacturing systems. The finished goods are produced in lots, and are then transported to a storage area in order to continuously meet a constant demand rate. The main objective of this work is to jointly determine the optimal lot sizing and optimal production control policy that minimise the total expected cost of inventory/backlog and transportation, over an infinite time horizon. The decision variables are the lot sizing and the production rate. The problem is formulated with a stochastic dynamic programming model and the impulse control theory is applied to establish the Hamilton–Jacobi–Bellman (HJB) equations. Based on a numerical resolution of the HJB equations, it is shown that the optimal control policy is governed by a base stock policy for production rate control and economic lot size for batch processing. A thorough analysis and practical issues are addressed with a simulation-based approach. Thus, a combined discrete–continuous simulation model is developed to determine the optimal parameters of the proposed policy when the failure and repair times follow general distributions. The results are illustrated with numerical examples and confirmed through sensitivity analysis. [ABSTRACT FROM PUBLISHER]

This paper discusses a production model for non-instantaneous Weibull deteriorating items with complete backlogging over an infinite time horizon and also extended to the finite time horizon. The model is studied under the production policy starting with shortages. The objective of this model is to minimise the total cost to the manufacturer which is the sum of the setup cost, production cost, holding cost and shortage cost. Finally, numerical examples are given to illustrate the real-life applications of the proposed model. Sensitivity analyses of the major inventory parameters are carried out. Some useful managerial applications are obtained by using sensitivity analysis. [ABSTRACT FROM PUBLISHER]

This paper focuses on the discrete-time automatic pipeline, inventory and order-based production control system (APIOBPCS), a well-established production and inventory control model. The feedback mechanism within the replenishment rule enables the model to mitigate the bullwhip effect, but introduces a stability problem. In this research, a comprehensive stability analysis is conducted for arbitrary lead times using difference equation theory. On the basis of stability, a state space approach is advocated to analyse the impact of replenishment parameters, demand processes, and lead times on the robustness of the bullwhip effect. The stability results demonstrate that the production control system can easily be destabilised without incorporating the work-in-progress (WIP) feedback loop. Furthermore, it reveals that the stability problem for long lead times can be simplified with the stability condition independent of the lead time. The results obtained in this study provide useful guidelines for the selection of replenishment parameters to guarantee stability and mitigate the bullwhip effect. [ABSTRACT FROM PUBLISHER]

This paper presents an algorithm portfolio methodology based on evolutionary algorithms to solve complex dynamic optimisation problems. These problems are known to have computationally complex objective functions, which make their solutions computationally hard to find, when problem instances of large dimensions are considered. This is due to the inability of the algorithms to provide an optimal or near-optimal solution within an allocated time interval. Therefore, this paper employs a bundle of evolutionary algorithms (EAs) tied together with several processors, known as an algorithm portfolio, to solve a complex optimisation problem such as the inventory routing problem (IRP) with stochastic demands. EAs considered for algorithm portfolios are the genetic algorithm and its four variants such as the memetic algorithm, genetic algorithm with chromosome differentiation, age-genetic algorithm, and gender-specific genetic algorithm. In order to illustrate the applicability of the proposed methodology, a generic method for algorithm portfolios design, evaluation, and analysis is discussed in detail. Experiments were performed on varying dimensions of IRP instances to validate different properties of algorithm portfolio. A case study was conducted to illustrate that the set of EAs allocated to a certain number of processors performed better than their individual counterparts. [ABSTRACT FROM PUBLISHER]

Responsive delivery without inefficient excess inventory requires short manufacturing cycle times. The manufacturing cycle time is comprised of operation time, loading/unloading time, set up time and machine idle time. The sum of loading/unloading, set up and machine idle times is called downtime. To shorten batch processing time, reduction in downtime must be the first priority. One way to reduce downtime per work unit is to increase batch quantity, while another is to shorten the sum of set up and machine idle times. Whereas fast cycle time is critical for time-based competition, efficient utilisation of labour is also essential to keep a manufacturing company competitive due to the rapid increase in labour costs. Therefore, in many small and medium-sized businesses, one worker simultaneously handles multiple machines. In such a shared worker environment, machine idle time inevitably occurs due to a lack of available workers. The purpose of this paper is to propose a downtime reduction method based on part sequencing in a shared worker environment. The proposed heuristic results in a significant reduction in average downtime when compared to the results from the existing optimal sequencing method of independent machines. [ABSTRACT FROM PUBLISHER]

Rate modifying activity (RM) is a type of maintenance after which the processing rate of the machine increases. RM is a very new topic in academic studies. However, it is very common in real world situations. In this paper, we study the integrated problem of assigning a common due-date to all jobs, scheduling the jobs and making decisions about the position of RM in a single machine environment in which the setup times are sequence dependent. The objective is minimising the summation of earliness costs, tardiness costs and due date related costs. This problem has never been studied in the literature with any arbitrary criterion. We construct a time-dependent travelling salesman problem (TDTSP) formulation for this problem. The position of the optimal common due date and some dominance properties for the position of RM are presented. A branch and bound (B&B) procedure is developed to solve the problem optimally. Numerical results justify the effectiveness of the B&B method for small problems. For larger problems, two robust metaheuristics are proposed. [ABSTRACT FROM PUBLISHER]

This paper presents an integrated computer simulation and Artificial Neural Network (ANN) algorithm for a stochastic Two-Stage Assembly Flow-Shop Scheduling Problem (TSAFSP) with setup times under a weighted sum of makespan and mean completion time (MCT) criteria, known as bi-criteria. Significantly, it should be noted that there is no mathematical model to analyse the stochastic model, therefore simulation is used to solve the problem. The simulation model enables decision makers to consider the influence of job scheduling on machines in order to examine both criteria simultaneously. Since it is not possible to evaluate all sequence combinations using the simulation model in a reasonable time, multilayered neural network meta-models have been trained and used to estimate objective function values composed of both makespan and mean completion time criteria for the stochastic TSAFSP. To the best of the authors’ knowledge, this is the first study that considers stochastic machine breakdown, processing times, setup times, makespan and mean completion time as objectives concurrently. The TSAFSP is modelled by Visual SLAM simulation software. The simulation output results are then given to the ANN as inputs to build the meta-model. This meta-model is then used to obtain the results with the optimum values. The advantage of these meta-model applications is a reduction in the number of simulation runs and consequently a reduced run time. Also, this is the first study that introduces an intelligent and flexible algorithm for handling stochastic TSAFSP. [ABSTRACT FROM PUBLISHER]

A new modelling approach is proposed for estimating storage/retrieval transaction times in warehouse systems using random storage and closest open location load dispatching. The method is based on estimating intervals between consolidations of the active storage envelope defined by the most remote occupied storage position in a warehouse. This enables the calculation of the expected number of interspersed storage vacancies within the storage envelope which can then be applied in transaction time calculations. Computational results for test problems suggest that the method performs well relative to alternative procedures reported in the literature. [ABSTRACT FROM PUBLISHER]

This paper considers a scheduling problem of heterogeneous transporters for pickup and delivery blocks in a shipyard assuming a static environment where all transportation requirements for blocks are predetermined. In the block transportation scheduling problem, the important issue is to determine which transporter delivers the block from one plant to the other plant and when, in order to minimise total logistic times. Therefore, the objective of the problem is to simultaneously determine the allocation policy of blocks and the sequence policy of transporters to minimise the weighted sum of empty transporter travel times, delay times, and tardy times. A mathematical model for the optimal solution is derived and an ant colony optimisation algorithm with random selection (ACO_RS) is proposed. To demonstrate the performance of ACO_RS, computational experiments are implemented in comparing the solution with the optimal solutions obtained by CPLEX in small-sized problems and the solutions obtained by conventional ACO in large-sized problems. [ABSTRACT FROM PUBLISHER]

In today's competitive scenario of increasingly faster deliveries and smaller order sizes, material-handling providers are progressively developing new solutions. A recent, automated material-handling technology for unit load storage and retrieval consists of an autonomous vehicle storage and retrieval system (AVS/RS). The present paper presents an analytical model to estimate the performances (the transaction cycle time and waiting times) of AVS/RS for product tote movement. The model is based on an open queuing network approach. The model effectiveness in performance estimation is validated through simulation. [ABSTRACT FROM PUBLISHER]

The cumulative count of conforming (CCC) chart as a main statistical process control tool for monitoring high-quality processes has been widely studied. However, its applicability is limited to situations where units of product are inspected sequentially, or item by item. Motivated by real-life problems, this paper proposes an improved control charting technique for high-quality processes under group inspection. It integrates a self-starting feature and an approximately ARL- (average run length) unbiased design. The chart, named the CCCG chart, monitors the cumulative count of conforming samples until a non-conforming one is encountered. The 'G' in the subscript stands for 'Group'. The self-starting feature caters to the need in practice to start monitoring a production process as soon as possible. The approximately ARL-unbiased design is developed to significantly improve the chart's sensitivity to process deterioration compared with the conventional design. The performance of the CCCG chart in phase I when the control limits are sequentially updated has been examined. Simulated data examples are presented to demonstrate the use and efficiency of the proposed technique. The CCCG chart is a natural generalisation of the traditional CCC chart and thus includes the latter as a special case. [ABSTRACT FROM AUTHOR]

In condition-based maintenance (CBM) with periodic inspection, the system is preventively replaced if failure risk, which is calculated based on the information obtained from inspection, exceeds a pre-determined threshold. The determination of optimal replacement threshold is often based on the minimisation of average maintenance costs per unit time due to preventive and failure replacements over a long time horizon. It is often assumed that inspections are performed at equal time intervals with no cost. However, in practice, inspections require labour, specific test devices, and sometimes suspension of operations and, thus, it is reasonable to inspect less frequently during the time the system is in its early age and/or in a healthier state and to perform inspections more frequently as time passes and/or as the system degrades. In other words, an age-based inspection scheme. This paper proposes a novel two-phase approach for the determination of an optimal replacement threshold and an optimal age-based inspection scheme for CBM such that the total long-run average costs of replacements and inspections are minimised. First, it takes into account failure and preventive replacement costs to determine the optimal replacement threshold assuming that inspections are performed at equal time intervals with no cost. This assumption is, subsequently, relaxed and its consequences on total average cost are evaluated using a proposed iterative procedure based on A* search algorithm to obtain the optimal age-based inspection scheme. The proposed approach is illustrated through a numerical example. [ABSTRACT FROM PUBLISHER]

The topic of representing the offset of a 2D B-spline curve in the same form has been a topic of research for a long time, and it has many industrial applications, especially in NC tool path generation for pocketing. For B-spline tool paths, it is often required that the tool paths have fewer control points, lower base function degree, and the approximation error is guaranteed within a given tolerance over the entire curve. However, the existing methods utilising global error control approximate the offsets of 2D free-form curves with high function degree and many control points. Although these offsets are useful in computer-aided design, they are inappropriate for the use of CNC machining. To address the problems in order to generate high quality B-spline tool paths, this original work formulates an error function of the offset approximation and then constructs a NURBS curve to globally bound the errors. By checking the maximum coefficient of the bounding curve, the upper bound of all the approximated offset errors is found and the errors can be reduced by segmenting the curve at appropriate knot values. The proposed new approach is more efficient, and the resulting offset approximations are more accurate, with fewer control points and lower function degree. It is useful to generate B-spline tool paths for CNC pocketing, which have the potential for other applications in industry. [ABSTRACT FROM PUBLISHER]

The purpose of this article is to test the performance of a heuristic algorithm that computes a quality control plan. The objective of the tests reported in this paper is twofold: (1) to compare the proposed heuristic algorithm (HA) to an optimal allocation (OA) method; and (2) to analyse the behaviour and limitations of the proposed HA on a scale-1 test with a before/after test. The method employed to evaluate this algorithm is based on comparisons: 1. The first test illustrates the method and its sensitivity to internal parameters. It is based on a simplified case study of a product from the semiconductor industry. The product is made up of 1000, 800 and 1200 wafers incorporating three different technologies. The production duration is 1 week, and three tools were involved in this test. The behaviour of the proposed algorithm is checked throughout the evolution of the model parameters: risk exposure limit (RL) and measurement capacity (P). The quality control plan for each tool and product are analysed and compared to those from a one stage allocation process (named C0) that does not take into account risk exposure considerations. A comparison is also performed with OA. 2. The second scale-1 test is based on three scenarios of several months of regular semiconductor production. Data were obtained from 23 etching and 12 photolithographical tools. The outputs provided by the HA are used in the sampling scheduler implemented at this plant. The resulting samples are compared against three indicators. The results of these comparisons show that, for small instances, OA is more relevant than the HA method. The HA provides realistic limits that are suitable for daily operations. Even though the HA may provide far from optimal results, it demonstrates major MAR improvement. In terms of the maximum inhibit limit, the HA achieves better performances than C0, and they are strongly correlated to RL and to the control capacity. The article concludes that the proposed algorithm can be used to plan controls and to guide their scheduling. It can also improve the insurance design for several levels of acceptance of risk. [ABSTRACT FROM AUTHOR]

This paper presents a conceptual design approach including pattern creation from designers, alternative exploration with a DOE matrix, alternative analysis via computer simulation and alternative selection by DEA analysis. Designers possessing domain knowledge create various design patterns to meet the requirements of product performance and customer expectations. Then, based on these design patterns, the alternatives, considered as decision-making units (DMUs), are extracted from various quality level combinations by following the use of the DOE matrix. The nature of the DOE matrix ensures that distinctive representatives are constructed for all design alternatives. The total alternatives (DMUs) consist of the alternatives associated with all the patterns. Computer simulation with ANSYS software is introduced to convert the quality level combination of each alternative (DMU) into simulated outputs, which are further categorised into DEA inputs and DEA outputs for DEA frontier analysis. Four DEA methods, CCR-min input, CCR-max output, BCC-min input and BCC-max output, are used for analysing typical market representatives resulting from market uncertainty. The found efficiencies are used to rank and select the explored alternatives (DMUs) for the next stage of the detailed design. A bike-frame product is chosen as an example to demonstrate the proposed approach. The results clearly show that the proposed approach enables designers to economically select appropriate design alternatives that satisfy performance expectations during the conceptual design stage. [ABSTRACT FROM PUBLISHER]

In this paper, two evolutionary heuristics are proposed to determine the cutting parameters in multipass turning operations. Optimal selection of cutting speed, feed rate, and depth of cut is important in machining operations due to significant influence of these parameters on machining quality and machining economics. This paper is about optimising these three parameters using heuristic methods. The first heuristic implemented in the paper is a simple Particle Swarm Optimisation (PSO) algorithm, and the second heuristic implemented is a hybrid of Genetic Algorithm and Artificial Immune System (GA-AIS). A multipass turning operation with rough machining and then finish machining is considered in this paper. The objective function considered is minimisation of unit production cost that optimises the machining parameters. The performance of the PSO and GA-AIS are evaluated by comparing with the heuristics reported in the literature using a problem set used by other researchers for this problem. The results are presented in tables and figures and indicates the better performance of GA-AIS over PSO and other heuristics reported in the literature. [ABSTRACT FROM PUBLISHER]

This research focuses on solving the multistage process push/pull junction point location problem. An aim is to implement a hybrid push/pull production system that can satisfy both high service‐levels and low inventory levels. Simultaneously, we consider sophisticated variability, such as multi‐products, random setup, indiscriminate break‐downs, yield loss, batch processes, and other contingencies. The problem can be solved by a multiple criteria decision‐making (MCDM) method. A technique for order‐preference by similarity‐to‐ideal solution (TOPSIS) is used to select a suitable option. The optimisation involves evaluation of stochastic performance measures within alternative scenarios among candidate junction‐point locations using a discrete event simulation model. A practical thin film transistor‐liquid crystal display (TFT‐LCD) process case‐study is utilised to illustrate the proposed method. After implementing a hybrid push/pull production strategy, simulation results indicate that the inventory level was reduced by over 18% while the service level remained about the same. For another scenario, a 3.4% decrease in service‐level can be paid off by a 46% decrease in inventory level and 34% improvement in lead time. [ABSTRACT FROM PUBLISHER]

The article focuses on the study of characteristics of digital geographical data and the influence of these characteristics on the quality of the basis being ready for the decision-making processes. Characteristics of digital geographical data are mainly described from the point of view of their technical parameters and keeping the technological indicators while obtaining them. Our system brings a user's view into the assessment of characteristics. We define user's requirements on data and suggest the system of their evaluation. The assessment of data characteristics comes out of the standard ISO 19113 and the theory of value analysis. Both systems are joined into a complex system for data evaluation. Technical characteristics of data are evaluated mainly by the level of accomplishment of qualitative indicators, e.g. meeting all requirements of horizontal and vertical mean square error, or by completeness of filling of all expected information. Meeting all users’ requirements is usually expressed by the level of user's satisfaction with the particular product. This level is set based on the survey among users. Simultaneously, the weight of the individual evaluating criteria is set according to specific types of solved tasks. The system of data evaluation is supplemented with a system of calculation of costs that are needed for obtaining the data. It is possible, however, to work either with the complete database, or to count also the influences of particular groups of data (e.g. communications, residential buildings, etc.) on the complete quality of the final product. The system of costs calculation and evaluation of data quality then enables the optimisation of the use of funds or disposable time for obtaining quality data. The use of the complete system is presented in a pilot project in which a model of terrain passability by a military heavy vehicle is solved. [ABSTRACT FROM PUBLISHER]

This paper describes a novel method for automated generation of process plans and numerical control (NC) part programs from 2D drawing image files. Four algorithms are introduced in this paper. First algorithm deals with extraction of geometrical data, second algorithm used to recognise turned features from the extracted geometrical data base. Recognised features are then passed to third and fourth algorithms for generation of process plans and NC part programs respectively. Using proposed system, it is possible to achieve fully automation of recognition of turned features, generation of process plans and NC part programs. Thus, it becomes possible to go from scanned image to finished product in a fully automated fashion. These algorithms have been implemented on mini-computer to process image data, and display recognised turned features, process plans and creates output files containing NC part programs. These NC part programs are verified through CNC train simulation package. The results are satisfactory. [ABSTRACT FROM PUBLISHER]

In a previous paper (Di Angelo, L., Di Stefano, P. and Morabito, A., 2011. Automatic evaluation of form errors in high-density acquired surfaces. International Journal of Production Research, 49 (7), 2061–2082) we proposed an original methodology for the automation of the geometric inspection, starting from an acquired high-density surface. That approach performed a recognition process on the acquired data aiming at the identification of some intrinsic nominal references. An intrinsic nominal reference was detected when a geometric property was recognised to be common to a set of adjacent points in the 3D data set representing the acquired object. The recognition of these properties was carried out based on some rules. Starting from these concepts, a new specification language was defined, which is based on recognisable geometric entities. This paper expands the category of intrinsic nominal references to include new mutual intrinsic orientation, location and dimensional properties pertaining to 3D features. This approach involves the automatic construction of a geometric reference model for a scanned workpiece, called recognised geometric model (RGM). The domain of the representable entities within the RGM strictly depends on the rules used for the recognition of the intrinsic properties. In particular, this paper focuses on the rules for the recognition of the orientation and location properties between non-ideal features. When using the RGM, tolerances are specified according to the set of available and recognisable intrinsic nominal references. Based on the geometric product specification, the RGM data structure can be queried to capture some quantitative information concerning special intrinsic geometric parameters and/or non-idealities. [ABSTRACT FROM PUBLISHER]

Object-oriented technology has been widely acclaimed as offering a revolution in computing that is resolving a myriad of problems inherent in developing and managing organisational information processing capabilities. Although its foundations arose in computer programming languages, object-oriented technology has implications for a wide range of business computing activities including: programming, analysis and design, information management, and information sharing. The problematic issues in the development of manufacturing software systems are related to the various characteristics of manufacturing systems, which are wide, dynamic and complex. Design for manufacturing (DFM) is the integrated practice of designing components while considering their manufacturability, and its benefits are widely acknowledged in the industry. A model has been developed using object oriented technology, after analysing the fundamental elements necessary for modelling manufacturing and process planning framework used in collaborative design and manufacturing in machine tool manufacturing. The main components of this model are: process planning model (PPM), manufacturing activity model (MAM), manufacturing resource model (MRM) and manufacturing cost and time model. We are using ontologies in conjunction with specific conceptual models, which can contribute to improve the interoperability between these models. The performance of this model is shown by means of one real world case. The developed manufacturing information based design tool integrated with an intelligence design system can be used for collaborative design and manufacturing, which will support machine tool designers’ to achieve cost effective and timely design. [ABSTRACT FROM PUBLISHER]

Multi-channel manufacturing (MCM) is a noteworthy approach offered as a kind of fractal manufacturing. Here cells are organised as channels. Machines are lined up to facilitate streamlined materials flow. Their replication in individual and separate channels is allowed. The machines are grouped in such a way to form channels that any product is prone to be produced at least in one channel. In addition, important parts are subject to production in more channels to prevent congestion. On the other hand, one-to-one association of operations to machines as in classical grouping techniques seems very restrictive. In fact any machine is capable of fulfilling more then one kind of task, and any operation is possibly accomplished in more than one kind of machine. In other words, compatible machines should not be overlooked. In this study, enhancing of MCM with compatible machines is aimed. Numerical experience has proved the superiority of the proposed method to form manufacturing cells. [ABSTRACT FROM PUBLISHER]

This paper deals with a flow-shop scheduling problem with limited intermediate buffer. Jobs are grouped in incompatible job families. Each job has to be processed by a batch processor followed by a discrete processor in the same order. The batch processor can process several jobs simultaneously so that all jobs of the same batch start and complete together. We assume that the capacity of batch processor is bounded. The batch processing time is identical for batches of the same family. A batch which has completed processing on the batch processor may block the processor until there is a free unit in the buffer. The objective is to determine a batching and scheduling for all jobs so as to minimise mean completion time. A lower bound and two heuristics algorithm are developed. Moreover, a two-stage method embedded with a Differential Evolution (DE) algorithm is also developed. DE is one of the latest evolutionary computation algorithms, which implements mutation, crossover, and selection operators to improve the candidate solutions iteratively. Three variants of DE are first compared with a continuous Genetic Algorithm employing the random key representation. Then, one variant of the DE with the best convergence speed is selected. Numerical experiments are conducted to evaluate the performances of the selected two-stage meta-heuristic and two heuristics. [ABSTRACT FROM AUTHOR]

Lot streaming is a technique of splitting production lots into smaller sublots in a multi-stage manufacturing system so that operations of a given lot can overlap. This technique can reduce the manufacturing makespan and is an effective tool in time-based manufacturing. Research on lot streaming models and solution procedures for flexible jobshops has been limited. The flexible jobshop scheduling problem is an extension of the classical jobshop scheduling problem by allowing an operation to be assigned to one of a set of eligible machines during scheduling. In this paper we develop a lot streaming model for a flexible jobshop environment. The model considers several pragmatic issues such as sequence-dependent setup times, the attached or detached nature of the setups, the machine release date and the lag time. In order to solve the developed model efficiently, an island-model parallel genetic algorithm is proposed. Numerical examples are presented to demonstrate the features of the proposed model and compare the computational performance of the parallel genetic algorithm with the sequential algorithm. The results are very encouraging. [ABSTRACT FROM AUTHOR]

Traditionally, design and manufacturing activities have taken place sequentially rather than simultaneously leading to inefficient and time consuming iterations between design and manufacturing stages. In order to expedite these iterations, manufacturability analysis systems (MASs) have been developed to allow the evaluation of various manufacturability aspects during the design stage and consequently to reduce the costs and time to market of the designed products. The definition, concepts, advantages of the MAS and its current state of development and applicability in the industrial environment are discussed in the introduction of the paper. Then, key issues and technologies related to the construction of a MAS such as methodologies applied in data input mechanisms, techniques for manufacturability reasoning and formats of the outputs generated by MASs are analysed. Furthermore, applicability of a MAS to various manufacturing processes and aspects such as manufacturability and fixturability indices that can be analysed and produced through a MAS are also commented. Disadvantages and limitations emerged from utilisation of MASs are critically analysed and presented. Finally, the paper concludes with discussion and suggestions for some prospective research trends and challenges in building and exploiting MASs. Particular attention is paid to the application of a MAS to micro-manufacturing processes on which, nowadays, both academics and industry are focusing their attentions for identifying future research and technological challenges and opportunities. [ABSTRACT FROM AUTHOR]

In a manufacturing system, reworking of the defectives and management of waste or scrap are important issues that call for immediate attention to meet the basic objectives and requirements for lean production system. This paper deals with a manufacturing process where finished goods are occasionally produced along with undesirable defective items and scrap. As the system is not always perfect, some scrap is produced during the manufacturing and/or rework processes. A rework process is necessary to correct the defective items into good finished products. The manufacturing process considered in this research deals with the process of rework that is performed 'within' the cycle. Also, three types of scrap detection scenarios are considered: (i) detection 'before' rework, (ii) detection 'during' rework, and (iii) detection 'after' rework. In order to avoid shortage of finished products due to scrap production, finished-product buffers have been considered to fulfil the customers' timely demand. The required finished products for these buffers are ordered from different suppliers. Based on the observations in shop floors, a number of inventory models are developed for a single-stage production process wherein defective items are reworked, and scraps are detected and discarded during entire process. For the stated detection procedures, the total cost functions for a single-stage imperfect manufacturing system are developed with 100% inspection to find the optimum operational policy for manufacturing batch sizes and economic storage of inventories. Numerical examples are used to demonstrate these models, and an analysis is performed to study the sensitivity of different system parameters on several measures of performance. [ABSTRACT FROM AUTHOR]

We use patent data from the worldwide semiconductor industry from 1984 to 1994 to study the effect of the structure of organizational knowledge bases, or the patterns of coupling between their elements of technical knowledge, on the usefulness of inventions and knowledge-base malleability. We argue that organizational variations in coupling patterns between knowledge elements can be reflected in a spectrum of knowledge-base structures--varying from fully decomposable (the knowledge base is composed of distinct clusters of knowledge elements coupled together with no significant ties between clusters) through nearly decomposable (knowledge clusters are discernable but are connected through cross-cluster couplings) to non-decomposable (no knowledge clusters emerge, as the couplings are pervasively distributed)--and that organizations may differ in the way they use their knowledge because of variations in their knowledge-base structure, rather than because of differences in the knowledge elements themselves. Results show that a nearly decomposable knowledge base increases the usefulness of the inventions generated from it, as measured by patent citations, and also the knowledge base's malleability or capacity for change. [ABSTRACT FROM AUTHOR]

Organic light emitting devices (OLEDs) have been the subject of intense research because of their potential for flat panel display and solid state lighting applications. While small molecule OLEDs with very high efficiencies have been demonstrated, solution processable devices are more desirable for large size flat panel display and solid state applications because they are compatible with low cost, large area roll-to-roll manufacturing process. In this review paper, we will present the recent progress made in solution processable OLEDs. The paper will be divided into three parts. In the first part of the paper, we will focus on the recent development of fluorescent polymer OLEDs based on conjugated polyfluorene copolymers. Specifically, we will present results of carrier transport and injection measurements, and discuss how the charge transport and injection properties affect the device performance. In the second part of the paper, we will focus on the recent progress on phosphorescent dye-dispersed nonconjugated polymer OLEDs. Specifically, we will present our recent results on high efficiency green and blue emitting devices based on the dye-dispersed polymer approach. Similar to fluorescent conjugated polymer OLEDs, charge transport and injection properties in dye-dispersed polymer OLEDs also play an important role in the device performance. In the third part of this paper, we will present our results on white emitting phosphorescent OLEDs. Two approaches have been used to demonstrate white emitting OLEDs. First, white emitting OLEDs were made using blue emitting OLEDs with downconversion phosphors. Second, white emitting OLEDs were made by dispersing red, green, and blue phosphorescent dyes into the light emitting layer. High efficiency devices have been demonstrated with both approaches. [ABSTRACT FROM AUTHOR]

This article identifies a methodological void in operations management (OM) research as the lack of empirical theory building. It addresses two questions: What is empirical science? and How can empirical theory building be nurtured in the area? The rationale for theory building in this article is derived from the classical empirical science perspective. Further, an empirically sound model OM theory is identified and evaluated, and selected theorylike statements and informal "theories" embedded in the OM literature are classified into an accepted classification scheme made up of grand theories, middle range theories, and empirical generalizations. [ABSTRACT FROM AUTHOR]

A multisite, multisource research methodology is suggested for students of corporate strategy in order to attain generalizability and statistical significance in reporting findings while not losing the nuances and under-standing of each firm's environmental context. A way of incorporating testable hypotheses into sampling designs is suggested and elements of the methodology are illustrated using extant strategy research publications. [ABSTRACT FROM AUTHOR]

The article discusses the relation between mass buying and mass selling. Specifically it discusses the relationship between chain stores and agricultural cooperatives. Early chain stores were based on the standardization of processed foods and the systemization of the retail business. The development of cooperatives sought to accomplish similar industrial standards. The cooperatives differed from chain stores in that all profits not put back into the business would be paid out consumers in patronage dividends.

Several recent developments in marketing information systems and analytical marketing models are described. These developments in combination with others reported in this JOURNAL OF MARKETING symposium will cast the future marketing executive in the role of a market engineer. He will have a heavier involvement in planning rather than doing, and in profit maximization. [ABSTRACT FROM AUTHOR]