Search results

1 – 10 of 100
Per page
102050
Citations:
Loading...
Access Restricted. View access options
Article
Publication date: 26 July 2011

Khairy A.H. Kobbacy, Hexin Wang and Wenbin Wang

Many supply contracts are employed in practice to improve the performance of supply chains. But there is a lack of research that can offer guidance to practitioners in choosing…

714

Abstract

Purpose

Many supply contracts are employed in practice to improve the performance of supply chains. But there is a lack of research that can offer guidance to practitioners in choosing the best supply contract among a group of popular contracts. This paper aims to fill this gap by developing an intelligent rule‐based supply contract design system for choosing the best contract and its parameters from a supplier's point of view.

Design/methodology/approach

The approach used in this paper is based on the comparison of several supply contracts that are encountered in supply chain practice. The paper aims at identifying the conditions under which one supply contract outperforms another from the supplier's perspective. To facilitate the implementation of the decision‐making rules that are developed in this research, an intelligent decision support system is developed.

Findings

Six popular contracts are analysed; returns policy (RP), quantity discount (QD), target rebate (TR), backup agreement (BA), quantity flexibility (QF), and quantity commitment (QC). The main findings are: QD contracts generate larger expected profits for the supplier than TR contracts do when the demand is exogenous, an RP contract is better than a QD contract when the wholesale profit margin is sufficiently large and that the optimal QC contract always provides a higher expected service level than BA and QF contracts.

Originality/value

The paper presents an approach for developing an intelligent supply contract design system that can offer guidance to practitioners in choosing the best supply contract for a particular supplier.

Details

Journal of Manufacturing Technology Management, vol. 22 no. 6
Type: Research Article
ISSN: 1741-038X

Keywords

Access Restricted. View access options
Article
Publication date: 1 June 1997

K.A.H. Kobbacy, D.F. Percy and B.B. Fawzi

Preventive maintenance (PM) is an effective maintenance policy which is widely applied in industry. Reviews the main approaches of modelling PM and discusses the characteristics…

1015

Abstract

Preventive maintenance (PM) is an effective maintenance policy which is widely applied in industry. Reviews the main approaches of modelling PM and discusses the characteristics of real life PM data which influence the methods for modelling PM. The most salient features of these data are the limited size and intensive censoring effect. Then introduces a parametric bootstrap method for fitting PM data to distributions. A simulation study to compare this method with the established Akaike and Schwarz criteria shows that while the bootstrap method is marginally better in identifying the true distribution, this is counterbalanced by the intensive computational effort needed.

Details

Journal of Quality in Maintenance Engineering, vol. 3 no. 2
Type: Research Article
ISSN: 1355-2511

Keywords

Access Restricted. View access options
Article
Publication date: 26 July 2011

Khairy A.H. Kobbacy and Sunil Vadera

The use of AI for operations management, with its ability to evolve solutions, handle uncertainty and perform optimisation continues to be a major field of research. The growing…

2686

Abstract

Purpose

The use of AI for operations management, with its ability to evolve solutions, handle uncertainty and perform optimisation continues to be a major field of research. The growing body of publications over the last two decades means that it can be difficult to keep track of what has been done previously, what has worked, and what really needs to be addressed. Hence, the purpose of this paper is to present a survey of the use of AI in operations management aimed at presenting the key research themes, trends and directions of research.

Design/methodology/approach

The paper builds upon our previous survey of this field which was carried out for the ten‐year period 1995‐2004. Like the previous survey, it uses Elsevier's Science Direct database as a source. The framework and methodology adopted for the survey is kept as similar as possible to enable continuity and comparison of trends. Thus, the application categories adopted are: design; scheduling; process planning and control; and quality, maintenance and fault diagnosis. Research on utilising neural networks, case‐based reasoning (CBR), fuzzy logic (FL), knowledge‐Based systems (KBS), data mining, and hybrid AI in the four application areas are identified.

Findings

The survey categorises over 1,400 papers, identifying the uses of AI in the four categories of operations management and concludes with an analysis of the trends, gaps and directions for future research. The findings include: the trends for design and scheduling show a dramatic increase in the use of genetic algorithms since 2003 that reflect recognition of their success in these areas; there is a significant decline in research on use of KBS, reflecting their transition into practice; there is an increasing trend in the use of FL in quality, maintenance and fault diagnosis; and there are surprising gaps in the use of CBR and hybrid methods in operations management that offer opportunities for future research.

Originality/value

This is the largest and most comprehensive study to classify research on the use of AI in operations management to date. The survey and trends identified provide a useful reference point and directions for future research.

Details

Journal of Manufacturing Technology Management, vol. 22 no. 6
Type: Research Article
ISSN: 1741-038X

Keywords

Access Restricted. View access options
Book part
Publication date: 18 January 2024

Zaheer Doomah, Asish Seeboo and Tulsi Pawan Fowdur

This chapter provides an overview of the potential use of Intelligent Transport Systems (ITS) and associated artificial intelligence (AI) techniques in the land transport sector…

Abstract

This chapter provides an overview of the potential use of Intelligent Transport Systems (ITS) and associated artificial intelligence (AI) techniques in the land transport sector in an attempt to achieve related United Nations Sustainable Development Goals (SDGs) targets. ITS applications that have now been extensively tested worldwide and have become part of the everyday transport toolkit available to practitioners have been discussed. AI techniques applied successfully in specific ITS applications such as automatic traffic control systems, real-time image processing, automatic incident detection, safety management, road condition assessment, asset management and traffic enforcement systems have been identified. These methods have helped to provide traffic engineers and transport planners with novel ways to improve safety, mobility, accessibility and efficiency in the sector and thus move closer to achieving the various SDG targets pertaining to transportation.

Details

Artificial Intelligence, Engineering Systems and Sustainable Development
Type: Book
ISBN: 978-1-83753-540-8

Keywords

Access Restricted. View access options
Article
Publication date: 1 July 2000

Farid Meziane, Sunil Vadera, Khairy Kobbacy and Nathan Proudlove

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their…

4687

Abstract

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence (AI) will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of AI techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different AI techniques to be considered and then shows how these AI techniques are used for the components of IMS.

Details

Integrated Manufacturing Systems, vol. 11 no. 4
Type: Research Article
ISSN: 0957-6061

Keywords

Access Restricted. View access options
Book part
Publication date: 12 September 2024

Dr Nitish Ojha and Dr Nikhil VP

It's no longer a secret that a hassle-free life and better human development index are only possible in smart cities with appropriate and efficient deployment of artificial…

Abstract

It's no longer a secret that a hassle-free life and better human development index are only possible in smart cities with appropriate and efficient deployment of artificial intelligence (AI)-based technologies where the best results of data analysis are being used. Technology is becoming more productive using circular economy while employing all the dimensions of AI where integration of results is being incorporated as an outcome of data analysis received from different segments i.e., Traffic Management, Public Safety, and Movement, Security and surveillance, Waste Management Systems, or the Energy Management, etc. This chapter specifically talks about areas where AI is facing challenges in the implementation and administration of smart cities while covering the intrinsic challenges faced in specialized domains such as Public Sanitation, Virtual Parking Management, Traffic Congestion, Security Surveillance, and many more discussed as case study relating to the functioning of the circular economy. In the last, we have summarized the impact of AI on the CE and its future scope where AI can play a better role in increased productivity, increased efficiency, robust safety and finally economic benefit for long-term stable economic stability, development and inclusive growth.

Access Restricted. View access options
Article
Publication date: 26 July 2011

Anna Ławrynowicz

The purpose of this research is to improve efficiency of the traditional scheduling methods and explore a more effective approach to solving the scheduling problem in supply…

901

Abstract

Purpose

The purpose of this research is to improve efficiency of the traditional scheduling methods and explore a more effective approach to solving the scheduling problem in supply networks with genetic algorithms (GAs).

Design/methodology/approach

This paper develops two methods with GAs for detailed production scheduling in supply networks. The first method adopts a GA to job shop scheduling in any node of the supply network. The second method is developed for collective scheduling in an industrial cluster using a modified GA (MGA). The objective is to minimize the total makespan. The proposed method was verified on some experiments.

Findings

The suggested GAs can improve detailed production scheduling in supply networks. The results of the experiments show that the proposed MGA is a very efficient and effective algorithm. The MGA creates the manufacturing schedule for each factory and transport operation schedule very quickly.

Research limitations/implications

For future research, an expert system will be adopted as an intelligent interface between the MRPII or ERP and the MGA.

Originality/value

From the mathematical point of view, a supply network is a digraph, which has loops and therefore the proposed GAs take into account loops in supply networks. The MGA enables dividing jobs between factories. This algorithm is based on operation codes, where each chromosome is a set of four‐positions genes. This encoding method includes both manufacture operations and long transport operations.

Details

Journal of Manufacturing Technology Management, vol. 22 no. 6
Type: Research Article
ISSN: 1741-038X

Keywords

Access Restricted. View access options
Article
Publication date: 1 June 1997

A.K.S. Jardine, D. Banjevic and V. Makis

States that the concept of condition‐based maintenance (CBM) has been widely accepted in practice since it enables maintenance decisions to be made based on the current state of…

1865

Abstract

States that the concept of condition‐based maintenance (CBM) has been widely accepted in practice since it enables maintenance decisions to be made based on the current state of equipment. Existing CBM methods, however, mainly rely on the inspector’s experience to interpret data on the state of equipment, and this interpretation is not always reliable. Aims to present a preventive maintenance policy based on inspections and a proportional hazards modelling approach with time‐dependent covariates to analyse failure‐time data statistically. Presents the structure of the software, currently under develop‐ ment and supported by the CBM Project Consortium.

Details

Journal of Quality in Maintenance Engineering, vol. 3 no. 2
Type: Research Article
ISSN: 1355-2511

Keywords

Access Restricted. View access options
Article
Publication date: 1 March 1996

David F. Percy and Khairy A.H. Kobbacy

Develops practical models for preventive maintenance policies using Bayesian methods of statistical inference. Considers the analysis of a delayed renewal process and a delayed…

1057

Abstract

Develops practical models for preventive maintenance policies using Bayesian methods of statistical inference. Considers the analysis of a delayed renewal process and a delayed alternating renewal process with exponential times to failure. This approach has the advantage of generating predictive distributions for numbers of failures and downtimes rather than relying on estimated renewal functions. Demonstrates the superiority of this approach in analysing situations with non‐linear cost functions, which arise in reality, by means of an example.

Details

Journal of Quality in Maintenance Engineering, vol. 2 no. 1
Type: Research Article
ISSN: 1355-2511

Keywords

Access Restricted. View access options
Article
Publication date: 1 October 2000

Francis K.N. Leung and Ada L.M. Cheng

In this study, a power law process (PLP) for the failures of an engine, regarded as a complex repairable system, in a minimal repair set‐up (i.e. only a small proportion of the…

1166

Abstract

In this study, a power law process (PLP) for the failures of an engine, regarded as a complex repairable system, in a minimal repair set‐up (i.e. only a small proportion of the constituent parts of the engine are replaced on repair) with the engine regularly replaced within period T or replaced at the Nth failure after its installation, whichever occurs first, was examined. First of all, the Laplace test was used to check for the existence of a deteriorating trend in the failure data. Second, model parameters of the PLP were estimated using the maximum‐likelihood estimation method. Third, the Cramer‐von Mises test was used to test its goodness of fit. Finally, the optimal replacement policy based on minimising the long‐run expected cost per month for each type of engine was determined. The statistical inference procedure involving the maximum‐likelihood method for the PLP is based on the associated large‐sample theory. This implies the need to have a lot of data before conducting a statistical analysis. Unfortunately, the authors do not have sufficient data to conduct a real statistical analysis and to bring a significant conclusion to the considered application. The paper describes an industrial application of a PLP and a theoretical replacement model.

Details

International Journal of Quality & Reliability Management, vol. 17 no. 7
Type: Research Article
ISSN: 0265-671X

Keywords

1 – 10 of 100
Per page
102050