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Publication date: 1 May 2019

Marco A. Bragadin and Kalle Kähkönen

This paper is based on research addressing quality of construction schedules. The paper aims to structure a Schedule Health Assessment method and present it as a means to…

Abstract

Purpose

This paper is based on research addressing quality of construction schedules. The paper aims to structure a Schedule Health Assessment method and present it as a means to carry out the evaluation of construction schedules.

Design/Methodology/Approach

The development of the Schedule Health assessment method can be characterised as constructive research. The structuring of the method is based on analysis of factors forming the overall quality of construction schedules. The method has been tested in a proof of concept study. This comprised a case study in which four master schedules developed by junior production managers were evaluated using the Schedule Health assessment method.

Findings

It is possible to construct a method for the quality evaluation of construction schedules.

Research Limitations/Implications

The completed testing is still rather limited since it is based merely on experiences of junior production managers with a single case.

Practical Implications

The Schedule Health assessment method can in a useful manner make the quality evaluation of construction schedules easy to approach and effective process.

Originality/Value

This research has produced a novel method for the quality evaluation of construction schedules.

Details

10th Nordic Conference on Construction Economics and Organization
Type: Book
ISBN: 978-1-83867-051-1

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Abstract

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Collaborative Risk Mitigation Through Construction Planning and Scheduling
Type: Book
ISBN: 978-1-78743-148-5

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Article
Publication date: 13 October 2021

Syed Asif Raza and Abdul Hameed

The findings of this study have lightened the focal research areas in maintenance planning and scheduling. These also served as effective guidelines for future studies in…

Abstract

Purpose

The findings of this study have lightened the focal research areas in maintenance planning and scheduling. These also served as effective guidelines for future studies in this area. This research, therefore, contributes in fulfilling the gap by carrying out an SLR of contemporary research studies in the area of models for maintenance planning and scheduling. At present, SLR rooted in BA has not been carried focusing on a survey over models for maintenance planning and scheduling. SLR uses advanced scientific methodologies from BA tools to unveil thematic structures.

Design/methodology/approach

We have systematically reviewed over 1,021 peer-reviewed journal articles. Advanced contemporary tools from Bibliometric Analysis (BA) are used to perform a Systematic Literature Review (SLR). First, exploratory analysis is presented, highlighting the influential authors, sources and region amongst other key indices. Second, the large bibliographical data is visualized using co-citation network analyses, and research clusters (themes) are identified. The co-citation network is extended into a dynamic co-citation network and unveils the evolution of the research clusters. Last, cluster-based content analysis and historiographical analysis is carried out to predict the prospect of future research studies.

Findings

BA tools first outlined an exploratory analysis that noted influential authors, production countries, top-cited papers and frequent keywords. Later, the bibliometric data of over 1,021 documents is visualized using co-citation network analyses. Later, a dynamic co-citation analysis identified the evolution of research clusters over time. A historiographical direct citation analysis also unveils potential research directions. We have clearly observed that there are two main streams of maintenance planning and scheduling applications. The first has focused on joint maintenance and operations on machines. The second focused on integrated production and maintenance models in an echelon setting for unrealizable production facilities.

Originality/value

There are many literature review-based research studies that have contributed to maintenance scheduling research surveys. However, most studies have adopted traditional approaches, which often fall short in handling large bibliometric data and therefore suffer from selection biases from the authors. As a result, in this area, the existing reviews could be non-comprehensive. This study bridges the research gap by conducting an SLR of maintenance models, which to the best of our knowledge, has not been carried out before this study.

Details

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

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Article
Publication date: 25 October 2021

Mandeep Kaur, Rajinder Sandhu and Rajni Mohana

The purpose of this study is to verify that if applications categories are segmented and resources are allocated based on their specific category, how effective scheduling

Abstract

Purpose

The purpose of this study is to verify that if applications categories are segmented and resources are allocated based on their specific category, how effective scheduling can be done?.

Design/methodology/approach

This paper proposes a scheduling framework for IoT application jobs, based upon the Quality of Service (QoS) parameters, which works at coarse grained level to select a fog environment and at fine grained level to select a fog node. Fog environment is chosen considering availability, physical distance, latency and throughput. At fine grained (node selection) level, a probability triad (C, M, G) is anticipated using Naïve Bayes algorithm which provides probability of newly submitted application job to fall in either of the categories Compute (C) intensive, Memory (M) intensive and GPU (G) intensive.

Findings

Experiment results showed that the proposed framework performed better than traditional cloud and fog computing paradigms.

Originality/value

The proposed framework combines types of applications and computation capabilities of Fog computing environment, which is not carried out to the best of knowledge of authors.

Details

International Journal of Pervasive Computing and Communications, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1742-7371

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Article
Publication date: 1 April 2004

Rong‐Lei Sun, Han Ding, Youlun Xiong and Runsheng Du

Dispatching rule‐based scheduling is a kind of dynamic scheduling commonly used in real world applications. Because of the lack of scheduling objective, it cannot optimize…

Abstract

Dispatching rule‐based scheduling is a kind of dynamic scheduling commonly used in real world applications. Because of the lack of scheduling objective, it cannot optimize the specific performances at which shop managers aim in the current production period. To overcome the limitations of the dispatching rule‐based scheduling, an iterative learning scheduling scheme is proposed in this paper. A scheduling objective function, which reflects the performance criteria in which the shop managers are most interested, is established and used to guide the optimization of the crucial performances. According to the value of the scheduling objective obtained from the last simulation period, the parameters are adjusted so as to decrease the objective during the next simulation period. Experimental results show that the iterative learning scheduling overcomes the limitations of the dispatching rule‐based scheduling and achieves higher performances.

Details

Journal of Manufacturing Technology Management, vol. 15 no. 3
Type: Research Article
ISSN: 1741-038X

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Article
Publication date: 1 June 1997

Ching‐Jong Liao and Chien‐Yuan Kao

Suggests that with the shortage of nursing personnel, hospital administrators have to pay more attention to the needs of nurses to retain and recruit them. Also asserts…

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1013

Abstract

Suggests that with the shortage of nursing personnel, hospital administrators have to pay more attention to the needs of nurses to retain and recruit them. Also asserts that improving nurses’ schedules is one of the most economic ways for the hospital administration to create a better working environment for nurses. Develops an algorithm for scheduling nursing personnel. Contrary to the current hospital approach, which schedules nurses on a person‐by‐person basis, the proposed algorithm constructs schedules on a day‐by‐day basis. The algorithm has inherent flexibility in handling a variety of possible constraints and goals, similar to other non‐cyclical approaches. But, unlike most other non‐cyclical approaches, it can also generate a quality schedule in a short time on a microcomputer. The algorithm was coded in C language and run on a microcomputer. The developed software is currently implemented at a leading hospital in Taiwan. The response to the initial implementation is quite promising.

Details

Health Manpower Management, vol. 23 no. 3
Type: Research Article
ISSN: 0955-2065

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Article
Publication date: 1 August 1994

Chao‐Lin Chang, Nicholas A.J. Hastings and Chris White

A fast production scheduling system, the very fast scheduler (VFS), hasbeen developed by the authors. It creates a capacity constrainedproduction schedule within one…

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1029

Abstract

A fast production scheduling system, the very fast scheduler (VFS), has been developed by the authors. It creates a capacity constrained production schedule within one minute of elapsed time for problems of a size encountered in industry. The quality of the schedules is comparable with the best alternative heuristic scheduling techniques. The speed of the scheduler is such that it can be used on a real‐time basis to plan capacity, adjust priorities and other parameters and derive new schedules.

Details

International Journal of Operations & Production Management, vol. 14 no. 8
Type: Research Article
ISSN: 0144-3577

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Article
Publication date: 1 February 1995

David Little, John Kenworthy, Peter Jarvis and Keith Porter

Work undertaken in collaboration with BPICS, Cincom (UK) Ltd andICI Engineering supported by funding from the EPSRC (CDP). The projectreviewed planning and scheduling

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1739

Abstract

Work undertaken in collaboration with BPICS, Cincom (UK) Ltd and ICI Engineering supported by funding from the EPSRC (CDP). The project reviewed planning and scheduling procedures in over 30 industrial companies over a two‐year period to establish best practice in shop‐floor scheduling and to identify the key factors for scheduling success. Outlines the research approach briefly to provide a framework for the analysis of scheduling performance by industrial sector and by scheduling tool. This includes a powerful method for the performance measurement of supply‐chain management systems which allows the comparison of effectiveness in different operating environments and when using a variety of scheduling approaches. Important elements of the project were the review and comparison of scheduling performance in conventional MRPII environments (usually a manual activity based on expediting or the use of shop floor control) with that of more recent finite capacity‐based tools and a classification of scheduling approaches. Some clear lessons have been learned. Concludes by presenting these along with an outline of the success factors which underpin effective scheduling performance in the range of best practice companies identified.

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Article
Publication date: 26 October 2012

S. Premalatha and N. Baskar

Machine scheduling plays an important role in most manufacturing industries and has received a great amount of attention from operation researchers. Production scheduling

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930

Abstract

Purpose

Machine scheduling plays an important role in most manufacturing industries and has received a great amount of attention from operation researchers. Production scheduling is concerned with the allocation of resources and the sequencing of tasks to produce goods and services. Dispatching rules help in the identification of efficient or optimized scheduling sequences. The purpose of this paper is to consider a data mining‐based approach to discover previously unknown priority dispatching rules for the single machine scheduling problem.

Design/methodology/approach

In this work, the supervised statistical data mining algorithm, namely Bayesian, is implemented for the single machine scheduling problem. Data mining techniques are used to find hidden patterns and rules through large amounts of structured or unstructured data. The constructed training set is analyzed using Bayesian method and an efficient production schedule is proposed for machine scheduling.

Findings

After integration of naive Bayesian classification, the proposed methodology suggests an optimized scheduling sequence.

Originality/value

This paper analyzes the progressive results of a supervised learning algorithm tested with the production data along with a few of the system attributes. The data are collected from the literature and converted into the training data set suitable for implementation. The supervised data mining algorithm has not previously been explored in production scheduling.

Details

Journal of Advances in Management Research, vol. 9 no. 2
Type: Research Article
ISSN: 0972-7981

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Article
Publication date: 21 August 2007

Wen‐Jinn Chen

In today's industry, a machine breakdown is common for a machine running a long period of time without maintenance. To avoid a sudden breakdown, periodic maintenance is…

Abstract

Purpose

In today's industry, a machine breakdown is common for a machine running a long period of time without maintenance. To avoid a sudden breakdown, periodic maintenance is usually performed in the production system. This paper aims to find a set of efficient schedules that considers both jobs and maintenance simultaneously.

Design/methodology/approach

This paper addresses a real‐life scheduling problem in a plastic company. An algorithm based on the variable range technique is developed to solve the problem by providing a small set of efficient schedules.

Findings

Once maintenance is performed, the job being processed must be stopped. This will result in some jobs being late or tardy and a relatively larger flow time is generated. Therefore, how to minimize these two criteria in the production system becomes an important issue in the company. Computational results show that problems with larger maintenance intervals and smaller maintaining time can produce a smaller number of efficient schedules.

Practical implications

It is seen that scheduling maintenance will result in some jobs being tardy and a larger flow time is generated. A decision maker can easily select a preferred schedule from the small set of efficient schedules. The proposed algorithm is appropriate not only for the studied company but also for those companies where periodic maintenance is required.

Originality/value

Presents an algorithm to find a small set of efficient schedules.

Details

Journal of Quality in Maintenance Engineering, vol. 13 no. 3
Type: Research Article
ISSN: 1355-2511

Keywords

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