A project scheduling approach to production planning with feeding precedence relations

Alfieri, Arianna; Tolio, Tullio; Urgo, Marcello

doi:10.1080/00207541003604844

Cited by 47 publications

(33 citation statements)

References 16 publications

(19 reference statements)

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“…Nevertheless, the authors concluded that the production flow in this context is driven by actual customer orders with the decoupling point (i.e., order penetration point -OPP) located at the design stage, as seen in Figure 1. Other expressions associated to this context are project manufacturing and multi-project organisations (Gademann & Schutten, 2005;Hans et al, 2007;Yang, 2013) where different projects are executed together competing for the same production resources (Herroelen & Leus, 2004;Chtourou & Haouari, 2008;Van de Vonder et al, 2008;Deblaere et al, 2011;Alfieri et al, 2011;Artigues et al, 2013).…”

Section: An Overview In Etomentioning

confidence: 99%

“…ETO products have deep and complex structures, with many assembly levels, needing coordination with component supply (Hicks & Braiden, 2000;Cameron & Braiden, 2004;Alfieri et al, 2011;Gosling & Naim, 2009; Grabenstetter & Usher, 2014). These products are super-value goods that are highly customised, produced in low volumes (often one-of-a-kind) and have a long engineering trajectory, with many disruptions and adaptations due to specification changes demanded by the customer (Hans et al, 2007;Pandit & Zhu, 2007;Alfieri et al, 2011;Powell et al, 2014).…”

Section: An Overview In Etomentioning

confidence: 99%

“…These products are super-value goods that are highly customised, produced in low volumes (often one-of-a-kind) and have a long engineering trajectory, with many disruptions and adaptations due to specification changes demanded by the customer (Hans et al, 2007;Pandit & Zhu, 2007;Alfieri et al, 2011;Powell et al, 2014). The production processes are typically non-repetitive yet labour intensive, often demanding highly skilled labour .…”

Section: An Overview In Etomentioning

confidence: 99%

See 2 more Smart Citations

An optimisation approach for capacity planning: modelling insights and empirical findings from a tactical perspective

Carvalho

Scavarda

Oliveira³

2017

Prod.

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The academic literature presents a research-practice gap on the application of decision support tools to address tactical planning problems in real-world organisations. This paper addresses this gap and extends a previous action research relative to an optimisation model applied for tactical capacity planning in an engineer-to-order industrial setting. The issues discussed herein raise new insights to better understand the practical results that can be achieved through the proposed model. The topics presented include the modelling of objectives, the representation of the production process and the costing approach, as well as findings regarding managerial decisions and the scope of action considered. These insights may inspire ideas to academics and practitioners when developing tools for capacity planning problems in similar contexts.

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Section: An Overview In Etomentioning

confidence: 99%

Section: An Overview In Etomentioning

confidence: 99%

Section: An Overview In Etomentioning

confidence: 99%

See 1 more Smart Citation

An optimisation approach for capacity planning: modelling insights and empirical findings from a tactical perspective

Carvalho

Scavarda

Oliveira³

2017

Prod.

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“…Another possible direction is to consider further variants of the precedence constraints. In Alfieri et al [1] and Bianco and Caramia [4] the following 4 types of constraints are considered: a) %Completed-to-Start (CtS) precedence: successor activity j can start its processing only when, in time period t, the fraction of predecessor activity i that has been processed is greater than or equal to f i j (Fig. 3(a)).…”

Section: Extensions and Further Developmentsmentioning

confidence: 99%

Hard Planning and Scheduling Problems in the Digital Factory

Kis

Drótos

2017

Math for the Digital Factory

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Production planning and scheduling with the aid of software tools in today's manufacturing industries have become a common practice which is indispensable for providing high level customer service, and at the same time to utilize the production resources, like workforce, machine tools, raw materials, energy, etc., efficiently. To meet the new requirements, problem modeling tools, optimization techniques, and visualization of data and results have become part of the software packages. In this chapter some recent developments in problem modeling and optimization techniques applied to important and challenging industrial planning and scheduling problems are presented. We will focus on new problem areas which are still at the edge of current theoretical research, but they are motivated by practical needs. On the one hand, we will discuss project based production planning, and on the other hand, we will tackle a resource leveling problems in a machine environment. We will present the problems, some modeling and solution approaches, and various extensions and applications.

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“…The estimation of the duration of production activities could be inaccurate, as well as their resource needs, the availability of machines, workers -or production resources in general -could vary, the supplying of raw materials or work-in-progress products could be late in relation to the scheduled time, new activities like rush orders or reworks could need to be executed with a higher priority (Cao et al, 2001;Alfieri et al, 2011;Makris and Chryssolouris , 2010;Mourtzis, et al, 2012;Nonaka, et al, 2012;Attia et al, 2014;Mogre et al, 2014). Hence, robust scheduling approaches have been developed, aiming at protecting the performance of a schedule by avoiding or mitigating the impact of uncertain events.…”

Section: Introduction and Problem Statementmentioning

confidence: 99%

A branch-and-bound approach for the single machine maximum lateness stochastic scheduling problem to minimize the value-at-risk

Urgo

Váncza

2018

Flex Serv Manuf J

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The research in the field of robust scheduling aims at devising schedules which are not sensitive -to a certain extent -to the disruptive effects of unexpected events. Nevertheless, the protection of the schedule from rare events causing heavy losses is still a challenging aim. The paper presents a novel approach for protecting the quality of a schedule by assessing the risk associated to the different scheduling decisions. The approach is applied to a stochastic scheduling problem with a set of jobs to be sequenced on a single machine. The release dates and processing times of the jobs are generally distributed independent random variables, while the due dates are deterministic. A branch-and-bound approach is taken to minimise the value-at-risk (VaR) of the distribution of the maximum lateness. The viability of the approach is demonstrated through a computational experiment and the application to an industrial problem in the tool making industry.

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A project scheduling approach to production planning with feeding precedence relations

Cited by 47 publications

References 16 publications

An optimisation approach for capacity planning: modelling insights and empirical findings from a tactical perspective

An optimisation approach for capacity planning: modelling insights and empirical findings from a tactical perspective

Hard Planning and Scheduling Problems in the Digital Factory

A branch-and-bound approach for the single machine maximum lateness stochastic scheduling problem to minimize the value-at-risk

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