Using real time information for effective dynamic scheduling

Cowling, Peter I.; Johansson, Marcus

doi:10.1016/s0377-2217(01)00355-1

Cited by 214 publications

(125 citation statements)

References 20 publications

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“…in the paper of Cowling and Johansson (2002) the simulationbased execution of the calculated schedules is introduced considering uncertain activity durations in the form of probability distributions. Regarding the robustness and flexibility of tardiness and total flow-time in job-shops, several schedule repair methods are investigated in (Jensen, 2001), and an experiment is performed on a set of benchmark problems by executing schedules against simulated machine breakdowns.…”

Section: Intensitymentioning

confidence: 99%

Simulation Support in Construction Uncertainty Management: a Production Modelling Approach

Pfeiffer

Kádár

Bohács

et al. 2016

Period. Polytech. Transp. Eng.

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The execution of construction projects such as a highway construction or the elevation of a new bridge is a complex, highly equipment-intensive process and are subject to many different uncertainties. This is very similar to the manufacturing execution level in production systems where predefined productions plans and schedules cannot be completely implemented due to unexpected internal and external changes and disturbances. Following this analogy, the paper proposes the application of a discrete-event simulation based method which was already applied in the decision-support for manufacturing control to develop the decision-support in the execution of a construction project where the effects of the deviation from the short-term schedule can be easily and quickly analyzed. Keywords Construction project, simulation, planning and scheduling, disturbance handling, uncertainty management IntroductionThe execution of construction projects such as a highway construction or the elevation of a new bridge is a complex, highly equipment-intensive process and are subject to many different uncertainties (Motawa et al., 2007). Capacity and availability of machinery and human resources, material supply, technology and precedence constraints, geographical and weather conditions are all important aspect in both planning and the execution of a construction project. Planning and scheduling of such projects are done a-priori taking into account the relevant resources, preliminary set-up activities, time, space and precedence constraints, etc. (Hinze, 2011). Nowadays, several different approaches and tools are applied to generate the longer-term plan and shorter-term, detailed schedule(s) of a construction project. The schedules which cover shorter periods like several days or weeks are subject to changes thus new and new schedules are generated on given-period basis (e.g. weekly) taking the finished operations and the new tasks to be performed into consideration. The need for change in the schedule the so-called rescheduling comes from the field manager's level where the monitoring and controlling of real-time construction activities are carried out. The milestones of the project are always kept in the longer-term plan and these plans are only changed if significant delays occur, which danger the achievement of milestones and success of the construction.The aspects enumerated above are analogous with the characteristics of production planning and scheduling and manufacturing shop-floor control, especially of those in project-base manufacturing. In the paper we propose the application of a discrete-event simulation based method which was already applied in the decision-support for manufacturing control. The method addresses the decision-support in the execution of a construction project where the effects of the deviation from the short-term schedule can be easily and quickly analysed.

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Section: Intensitymentioning

confidence: 99%

Simulation Support in Construction Uncertainty Management: a Production Modelling Approach

Pfeiffer

Kádár

Bohács

et al. 2016

Period. Polytech. Transp. Eng.

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“…The event handling process typically consists of the following stages in practice: detection, identification, evaluation, diagnosis and decision making: When an unexpected event occurs it should be first detected by automated technologies or humans like operators [3]. The identification stage underlies the causes of the deviation, the context of the event for priority determination [15], and determines the relevant parties and information to handle the event.…”

Section: Event Handling Process and Underlying Factorsmentioning

confidence: 99%

“…that must be captured and responded effectively, namely timely and appropriately [2]. However, the difficulty of addressing the issue of uncertainty in dynamic manufacturing environments is well recognized by researchers and practitioners for many decades [3][4][5]. Hence, this study questions: What important factors have been identified in literature to handle the unexpected events effectively and what insights can we get from companies, regarding the event handling process and identified factors?…”

Section: Introductionmentioning

confidence: 97%

Handling Unexpected Events in Production Activity Control Systems

Arica¹,

Strandhagen²,

Hvolby³

2013

IFIP Advances in Information and Communication Technology

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Abstract. This paper highlights the important factors that influence the effectiveness of the event handling process in production control activity (PAC). Five key factors have been identified by the literature study. Production schedule generation and execution strategy under uncertainty, information and communication technology usage, coordination and feedback, human factor and interaction, and the performance measurement approach are the identified factors to be taken into account. Industrial interviews with three case companies, that are participating to the research program called The Norwegian Manufacturing Future (SFI NORMAN), have been carried out in order to gain practical insights as well as support and revise the findings by relevant empirical data.

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“…The analytical solutions proposed in [25] are able to estimate important performance measures for schedule evaluation methods in a dynamic, stochastic manufacturing system, and are evaluated in simulation testbeds. In [4] and [6] the simulation-based execution of the calculated schedules is introduced considering uncertain activity durations in the form of probability distributions. Regarding the robustness and flexibility of tardiness and total flow-time in job-shops, several schedule repair methods are investigated in [12], and an experiment is performed on a set of benchmark problems by executing schedules against simulated machine breakdowns.…”

Section: Production Control and Simulationmentioning

confidence: 99%

Digital enterprise solution for integrated production planning and control

Monostori

Erdös

Kádár

et al. 2010

Computers in Industry

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Digital enterprise technologies combined with sophisticated optimization algorithms can significantly contribute to the efficiency of production. The paper introduces a novel approach for integrated production planning and control, with the description of the mathematical models and solution algorithms. The deterministic optimization algorithms are complemented by a discrete-event simulation system to assess solution robustness in case of disturbances. The methods are illustrated by describing two prototype systems and by some experimental results obtained in an industry initiated project.

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Using real time information for effective dynamic scheduling

Cited by 214 publications

References 20 publications

Simulation Support in Construction Uncertainty Management: a Production Modelling Approach

Simulation Support in Construction Uncertainty Management: a Production Modelling Approach

Handling Unexpected Events in Production Activity Control Systems

Digital enterprise solution for integrated production planning and control

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