Showing papers in "European Journal of Industrial Engineering in 2008"

A novel differential evolution algorithm for no-idle permutation flow-shop scheduling problems

Abstract: A novel Discrete Differential Evolution (DDE) algorithm is proposed in this paper for solving no-idle permutation flow-shop scheduling problems with maximum completion time (makespan) criterion. Firstly, individuals of the DDE algorithm are represented as discrete job permutations, and new mutation and crossover operators are developed. Secondly, a local search algorithm based on insert neighbourhood is embedded in the DDE algorithm to balance the exploration and exploitation and to enhance the local searching ability. In addition, we present two simple approaches to calculate makespan and a speed-up method for insert neighbourhood to improve the efficiency of the whole algorithm. Computational simulations and comparisons based on some well-known benchmarks demonstrate that the DDE algorithm is not only superior to the improved greedy and Kalczynski-Kamburowski heuristics in terms of searching quality, but also superior to the particle swarm optimisation and differential evolution algorithms according to searching quality, robustness and efficiency. [Received 9 July 2007; Revised 10 October 2007; Accepted 30 October 2007]

A survey of the literature on the multiple or parallel assembly Line balancing problem

Abstract: This paper focuses on production systems that consist of multiple parallel assembly lines. The main literature contributions are briefly described and used to present a summary of the state of the art. The advantages and disadvantages of adopting multiple lines are discussed and the multiple assembly line balancing problem and its relevant characteristics are described.

Operating theatre scheduling using Lagrangian relaxation

Abstract: This paper addresses the surgery operation scheduling problem. Three types of resources are considered: transporters, operating rooms and recovery beds. The patient is first transported from the ward to the operating theatre, is operated on in an operating room and then transferred immediately to a recovery bed before being transported back to the ward. The operating room needs to be cleaned after the surgery before starting another operation. The problem consists in assigning patients to transporters, operating rooms and recovery beds in order to minimise a criterion function of their completion times. The problem is NP-hard. A Lagrangian relaxation approach is proposed to determine a near-optimal schedule and a tight lower bound. Numerical results will be presented to show the efficiency of the method.

Forming relationships with stakeholders in engineering projects

Abstract: For a project manager, it is vital to build good relations with the stakeholders who are identified as being most crucial in the project process and in using the final results of the project. The purpose of this paper is to study relationships in an engineering project setting; more specifically, the focus is on identifying the determining factors that form the relationship between the project and its stakeholders. This paper presents an empirical study based on in-depth interviews following a semistructured approach. Three engineering projects were studied in detail. Results from the current study identified five different types of relationships: classical market; through a third party; open and direct; integrated team; and partnering. Another finding indicates that five different factors have an impact on the formation of the project-stakeholder relationship: trust; uncertainty and control; culture and language; resources and knowledge; and goal congruence. [Received 15 May 2007; Revised 15 August 2007; Accepted 30 August 2007]

The splittable pickup and delivery problem with reloads

Abstract: In this paper, we consider a variant of the Pickup and Delivery Problem (PDP), where any demand may be dropped off elsewhere other than its destination, picked up later by the same or another vehicle, and so on until it has reached its destination. We discuss the complexity of this problem and present two mixed-integer linear programming formulations based on a space-time graph. We describe some valid inequalities for the problem along with separation routines. Based on these results, we develop a branch-and-cut algorithm for the problem, and present some computational results.

A study on human-task-related performances in converting conveyor assembly line to cellular manufacturing

Abstract: In this paper, we propose a study to analyse the human-task-related performances in converting a Conveyor Assembly Line (CAL) to cellular manufacturing, which include the possible added operational tasks (which is considered a negative factor for the conversion), the skill level and the cross-training of workers. Three theoretical models (CAL, cellular manufacturing and a joint type, CAL+CM) are constructed involving those constraints respectively. A human-factor-based training approach is also represented for the system performance improvement in cellular manufacturing. Assuming the product mix and the skill level of workers are probability variables, simulation experiments based on the data collected from the previous documents are then used to estimate the marginal impact each factor change had on the estimated performance improvement resulting from the conversion. [Received 18 January 2007; Revised 13 July 2007; Accepted 26 July 2007]

Estimating parameters of the three-parameter Weibull distribution using a neural network

Abstract: Weibull distributions play an important role in reliability studies and have many applications in engineering. It normally appears in the statistical scripts as having two parameters, making it easy to estimate its parameters. However, once you go beyond the two parameter distribution, things become complicated. For example, estimating the parameters of a three-parameter Weibull distribution has historically been a complicated and sometimes contentious line of research since classical estimation procedures such as Maximum Likelihood Estimation (MLE) have become almost too complicated to implement. In this paper, we will discuss an approach that takes advantage of Artificial Neural Networks (ANN), which allow us to propose a simple neural network that simultaneously estimates the three parameters. The ANN neural network exploits the concept of the moment method to estimate Weibull parameters using mean, standard deviation, median, skewness and kurtosis. To demonstrate the power of the proposed ANN-based method we conduct an extensive simulation study and compare the results of the proposed method with an MLE and two moment-based methods.

On the choice of a demand distribution for inventory management models

Abstract: An inventory system containing uncertainty, e.g., in demand, in costs, in lead time, or in supplied quantity or quality, needs a probability distribution of demand for reorder point models. In the literature on inventory control, many times reference is made to the Normal or Gamma distribution for describing the demand in the lead time. The Poisson distribution has been found to provide a reasonable fit when the demand is very low. However, information about the functional form of the probability distribution is often incomplete in practice. For example, it might be that only the first moments of the probability distribution are known. This incomplete information is a problem as the shape of the distribution is important in terms of the performance of inventory control. A procedure is described to determine shape characteristics when only the first two moments of the distribution of demand during the lead time are known, using a compound Poisson distribution and the Pearson chart. [Received 18 August 2006; Revised 15 November 2007; Accepted 11 February 2008]

An unrelated parallel machines model for an industrial production resetting problem

Abstract: Efficient production resettings are necessary to achieve production flexibility. For this reason, most modern companies are trying to reduce the setup time required to switch the production from one product type to another. One way to minimise these times is to schedule correctly the various tasks involved during a production resetting: changing tools, modifying each machine setting, etc. In this paper, we present how this problem can be identified to an unrelated parallel machines problem with release dates and delivery times where the resources are operators. We show that the data structure allows simplifying the problem into an assignment problem, even when we take into consideration the availability constraints of the operators. A branch-and-bound method is presented which has been tested on industrial and generated instances. [Received 6 February 2007; Revised 22 August 2007; Accepted 11 November 2007]

Multi-item, economic order quantity model with permissible delay in payments and a budget constraint

Abstract: This paper investigates the optimal replenishment policy for multi-item ordering under the conditions of permissible delay in payment, a budget constraint and permissible partial payment at a penalty. Such conditions exist in the use of purchase cards to order merchandise directly from the supplier. The paper presents mathematical models and closed form solutions for three situations ? permissible delay is negative (payment made before receipt of good), is less than the replenishment interval and is greater than the replenishment interval. The analyses indicate that it is more economical for the purchaser to make entire payments even when the interest earned is greater than the interest charged. [Received 06 April 2007; Revised 02 December 2007; Accepted 23 January 2008]

A time-varying lot size method for the economic lot scheduling problem with shelf life considerations

Abstract: Most studies on the economic lot scheduling problem with shelf life considerations adopt the common cycle approach which usually gives a result with high cost. Basic period method has been applied to this problem recently resulting in a lower cost. This paper takes a time-varying lot size approach. Two models are formulated to optimise the production schedule for any given production sequence, one assuming that production of each product starts only when the inventory of this product becomes zero, and the other relaxing this restriction. To generate production sequences, we use an existing heuristic and also develop a new heuristic. Numerical experiments on a benchmark problem show that at all the utilisation levels tested the new method outperforms previous methods. Further experiments show that the production frequencies for the products, production sequence and a less restricted scheduling model all contribute to the low production cost.

An ant colony algorithm for cell-formation in cellular manufacturing systems

Abstract: In this paper, we consider the problem of cell-formation in cellular manufacturing systems with the objective of maximising the grouping efficacy. We propose an Ant-Colony Optimisation (ACO) algorithm to obtain machine-cells and part-families. The Proposed ACO (PACO) algorithm is tested by using many benchmark data sets. The grouping efficacy obtained by the PACO algorithm for a given benchmark problem instance is compared with the grouping efficacies obtained by the existing approaches. The comparison shows that the PACO performs very well in maximising the grouping efficacy. [Received: 2 May 2007; Revised: 1 November 2007; Accepted: 3 December 2007]

Spare parts criticality for unplanned maintenance of industrial systems

Abstract: The paper presents a methodology and Decision Support System (DSS) for the establishment of spare parts criticality with a focus on industrial unplanned maintenance needs. The obtained criticality is used to rationalise the efficiency of the plant spare parts inventory. Through a top-down Failure Modes Effects and Criticality Analysis (FMECA) that is appropriately adapted to the unplanned maintenance requirements and through the introduction of the Component Dynamic Criticality concept, the components of an industrial production facility are ranked. For those with criticality lying above a calculated threshold, additional spares are suggested to be kept in the plant spare parts inventory. An application example demonstrates the method. [Received 14 May 2007; Revised 25 July 2007; Accepted 13 September 2007]

A methodology to enhance equipment performance using the OEE measure

Abstract: In recent years, a remarkable improvement has taken place in the maintenance management of physical assets and productive systems to reduce the wastage of energy and resources. The Overall Equipment Effectiveness (OEE) methodology is a proven approach to increase the overall performance of equipment. Focused improvement and autonomous maintenance are two important activities to enhance equipment performance. These activities aim to educate the participants in the concepts and philosophy of equipment maintenance and give them an opportunity to develop their knowledge and skills. The OEE of the machine needs to be higher for sustained capacity planning. In the present paper, a method is proposed to evaluate OEE by including a factor known as usability and a relation is developed to evaluate the earning capacity of six big losses with incremental improvement in OEE as an extension to the maturity of OEE. Furthermore, a framework is proposed for implementing the OEE methodology to enhance overall equipment performance. [Submitted 30 April 2007; Revised 12 October 2007; Accepted 17 December 2007]

Deadlock.free scheduling of flexible job shops with limited capacity buffers

Abstract: In this paper, Mixed Integer Programming (MIP) formulations of the deadlock-free job shop scheduling problem are proposed. The presence of buffer space with limited capacity is considered. This research work also proposes a novel operations insertion algorithm based on the rank matrix (or Latin rectangle). In this algorithm, rank matrices are used to generate the schedules and to check for deadlock situations. Finally, an insertion algorithm is proposed to insert transportation operations in the obtained schedules. Performance evaluations of the proposed mathematical models and the proposed algorithm are conducted. The results show that the mathematical models outperform a model presented earlier in the literature. The results also show that the proposed algorithm obtains the same or better solutions when compared to other solution methodologies reported in the literature. [Submitted 31 July 2007; Revised 14 October 2007; Accepted 14 October 2007]

The reference installation approach for the estimation of industrial assets at risk

Abstract: When natural disasters and extreme events such as storms, floods and earthquakes occur, it is not only people, residential buildings and infrastructure that are seriously affected, but also industry. Direct losses to installations as well as indirect losses, e.g., the interruption of production, can cause severe damage to companies and the economy as a whole. For a comparative and quantitative risk assessment, and being a prerequisite for

An adaptive algorithm for the knapsack problem: perturbation of the profit or weight of an arbitrary item

Abstract: This paper solves the binary single-constrained Knapsack Problem (KP) and undertakes a sensitivity analysis of its optimum solution. Given a knapsack of capacity c, and a set of n items, with each item j, j = 1,?,n, characterised by a weight wj and a profit pj, the binary single-constrained KP picks a subset of these items with maximal total profit while obeying the constraint that the maximum total weight of the chosen items does not exceed c. This paper proposes an adaptive branch and bound tree search algorithm that exactly solves the problem, and provides the limits of the sensitivity intervals, which guarantee the stability of the optimal solution when the profit of any arbitrary item is perturbed. Next, the paper adapts the exact algorithm for the perturbation of the weight coefficient of an arbitrary item. The computational results demonstrate the effectiveness of the adaptive algorithm. [Received: 16 March 2007; Revised: 08 August 2007; Accepted: 16 November 2007]

Heuristic approaches for determining minimum cost delivery quantities in supply chains

Abstract: In this paper, we consider heuristic approaches for the determination of delivery quantities in a Supply Chain (SC). The problem under consideration is important for the design of delivery quantity negotiations between manufacturers and suppliers. We describe a Mixed Integer Programming (MIP) formulation for the optimisation problem to be solved. We explain how we can incorporate and use the suggested decision model into a decision-support system for Supply Chain Management (SCM). Because of the computational intractable large-sized mixed integer programs, we describe an efficient Genetic Algorithm (GA) in order to get near-to-optimal solutions of the mixed integer programs. We compare the GA with a Random Search Heuristic and a Branch and Bound (BB Revised 01 June 2007; Second Revision Received 06 October 2007; Accepted 06 December 2007]

Optimising the service capacity by using a speed-up simulation

Abstract: In this work we provide an effective method based on a speed-up simulation+optimisation tool that allows us to optimise the capacity of a queue model system subject to the completion of a Quality of Service (QoS) criterion. This criterion is expressed in terms of a very small probability of losing a customer due to system overload. To evaluate the performance of the system, multiple simulations with different capacity levels have to be made. Because of the characteristics of these kinds of systems, any speed-up tool will be necessary in order to keep the computational time reasonably bounded. Our tool uses a speed-up technique, called RESTART, once and it does not need another entire execution of the method when a new capacity level is considered. Our tool only requires a stage (partial execution) of the RESTART method in order to update the probabilities when the capacity of the system is changed, so this involves a considerable saving of computational time. [Submitted 6 November 2007; Revised 25 January 2008; Accepted 25 January 2008]

Lot-splitting for inspection in a synchronised two-stage manufacturing process with finite production rates and random out-of-control shifts in the first stage

Abstract: We consider a non-repetitive manufacturing environment where the first stage will successively process different types of items that require different set up modes. Optimal sublot sizes are determined by studying the trade-off between the cost and time spent in restoration and rework. In addition, we discuss the resulting economical batch sizes, number of sublots, and processing rates. Finally, we provide recommendations on how to design the material handling flow system to implement our suggested inspection policies. Some of the managerial implications we found is that quality improves significantly when Stage 2 is more responsive (has faster processing times) than Stage 1 and when large batch sizes are divided into more sublots. Depending on the relative magnitude of poor quality and rework costs, we show that there is a threshold for the batch size under which sublot formation becomes inefficient. ]Received 17 July 2007; Revised 30 September 2007; Accepted 12 October 2007]

Demand signal modelling: A short-range panel forecasting algorithm for semiconductor firm device-level demand

Abstract: A model-based approach to the forecasting of short-range product demand within the semiconductor industry is presented. Device-level forecast models are developed via a novel two-stage stochastic algorithm that permits leading indicators to be optimally blended with smoothed estimates of unit-level demand. Leading indicators include backlog, bookings, delinquencies, inventory positions, and distributor resales. Group level forecasts are easily obtained through upwards aggregation of the device level forecasts. The forecasting algorithm is demonstrated at two major US-based semiconductor manufacturers. The first application involves a product family consisting of 254 individual devices with a 26-month training dataset and eight-month ex situ validation dataset. A subsequent demonstration refines the approach, and is demonstrated across a panel of six high volume devices with a 29-month training dataset and a 13-month ex situ validation dataset. In both implementations, significant improvement is realised versus legacy forecasting systems. [Received 11 May 2007; Revised 5 September 2007; Accepted 15 October 2007]

Modelling and solving a multimode and multisite industrial problem: Lagrangean relaxation and heuristic approaches

Abstract: In this paper, we tackle the problem of scheduling multisite and multimode activities in order to minimise the project duration that meets the constraints imposed by limited resources. The industrial system is composed of many production sites, and each site has its own resources called local resources, and every site can receive resources called global resources. The objective is to support the repartition of all the lots of pieces on different sites in a cooperative way, and to assign resources. The system reduced to only one site highlights the well-known problem of the Multimode Resource-Constrained Project Scheduling Problem (MRCPSP). We propose a mathematical programming approach based on competitive feasible solutions and strong lower bounds, within quite reasonable computation times. The basic ingredients of this approach are the Lagrangean relaxation. We also propose a method based on stochastic descent with restart to compute large-sized industrial instances. The experiments show that this technique gives solutions close to the optimum. This seems to indicate that these resolution methods are good candidates for real industrial problems.

Generic approach for the customisation of the TPM programme: using the process transformation model and reliability assessment tool

Abstract: This paper describes a generic method for the development and design of a TPM programme that is best suited to the organisation's needs. The research starts with an extensive review of literature on Total Productive Maintenance (TPM), which led to the formation of a model for the introduction of TPM to an organisation. A case study was conducted, which includes empirical research at the plant level to validate the proposed model and methodology as well as demonstrate its usability and application. The findings were subsequently analysed using the 'reliability assessment method'. The results demonstrate the effectiveness of the method in providing a quantified assessment of the outcome at each stage of the TPM introduction process and help to identify various key factors for its success. It is, therefore, important for the readers, both academic and practitioner, to understand the proposed approach for supporting firms to managing TPM from concept to implementation. [Received 23 April 2007; Revised 11 July 2007; Accepted 27 December 2007]

Establishment of semiconductor equipment purchasing evaluation model based on a knowledge management database

Abstract: The conventional method for selecting a suitable equipment supplier may have disadvantages such as failing to consider the supplier's technical experience and knowledge and inability of supplier management to make further forecast analysis to aid the decision maker in strategy optimisation. The investment in equipment is expensive but is the key success factor in semiconductor manufacturers' maintaining a competitive advantage. Moreover, in order to effectively evaluate the candidate equipment of suppliers, it is critical to include an evaluation of a candidate supplier's historical and test data. This research constructed an explicit knowledge Semiconductor Equipment Evaluation Model (SEEM) primarily to extract tacit supplier knowledge in fulfilling the semiconductor equipment purchase process. SEEM integrates the analytical hierarchy process, grey relational analysis and knowledge management database. The proposed model supplements the conventional method that considers only qualitative criteria or acquisition cost and provides transparency in the purchasing information and process. [Received 31 May 2007; Revised 18 July 2007; Accepted 26 July 2007]