A reactive decision-making approach to reduce instability in a master production schedule

Herrera, Carlos; Belmokhtar-Berraf, Sana; Thomas, André; Parada, Víctor

doi:10.1080/00207543.2015.1078516

Cited by 28 publications

(15 citation statements)

References 33 publications

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“…They determine the changes, particularly change in production plan date or change in production quantity. These findings support previous studies by many researchers including Herrera et al , (2016), Pujawan et al (2014) and Sivadasan et al , (2013) that point out demand uncertainty as one of the sources of schedule instability or nervousness.…”

Section: Discussionsupporting

confidence: 91%

Analysis of production planning in a global manufacturing company with process mining

Arsad

Astuti

et al. 2018

JEIM

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Purpose The purpose of this paper is to present the result of using process mining to model the production planning (PP) process of a manufacturing company that is supported by enterprise resource planning (ERP) systems. Design/methodology/approach This paper uses event logs obtained from the case company’s ERP database. The steps for this research are planning process mining implementation, extraction and construction of event log, discovering process model with Heuristic Miner and analysis. Findings Process model obtained from process mining shows how the PP is actually conducted. It shows the loop in materials requirement planning and create plan order process. Furthermore, the occurrences of changing plan order date and production line indicate the schedule instability in the case company. Further analysis of the material management (MM) event log shows the implication of production plan changes on MM. Continuous change in the plan affects material allocation priority and may result in a mismatch between production needs and the materials available. Research limitations/implications The study is only conducted in a single and specific case. Therefore, even though the findings provide good insight, the use of solitary case study does not imply a general result applied to other cases. Hence, there is a need to conduct similar studies on various cases so that a more generic conclusion can be drawn. Practical implications The result provides insights into how the current company’s policy of adjusting the production plan to accommodate changing demand impacts their operation. It can help the company to consider a better balance between flexibility and efficiency to improve their process. Originality/value The paper demonstrates the use of process mining to capture the real progression of PP based on the data stored in the company’s ERP database, which give an insight into how a real company conducts their PP process, the implication of schedule instability on MM and production. The novelty of this research lies in the use of process mining to attest to the schedule nervousness issue at a process level.

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Section: Discussionsupporting

confidence: 91%

Analysis of production planning in a global manufacturing company with process mining

Arsad

Astuti

et al. 2018

JEIM

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“…A master production program should be periodically adjusted according to demand, and as a consequence, a phenomenon known as nervousness generates instability in the production schedule. Nervousness is defined as a character in a Master Resource Planning (MRP) system when minor changes in higher-level records or the master production schedule cause significant timing or quantity changes in lower-level schedules and orders [20] [21].…”

Section: Materials Requirement Planning (Mrp)mentioning

confidence: 99%

Production Capacity Requirements Planning Using The Capacity Method Requirement Planning

Permana

Andriani

Dewiyana

2021

Int. J. Eng. Scie. and Inform. Technology.

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PT. ABC is a company engaged in the manufacture of Dolomite Fertilizer. The number of requests is greater than the amount of production. Due to fluctuations in the number of requests that tend to increase, this occurs due to a lack of capacity at the workstation. Therefore, it is necessary to calculate the capacity requirements planning analysis for each work station to know the company's capacity needs. The research aims to identify the shortage/excess production capacity and provide proposals for the balance of production capacity at PT. A B C. Production capacity research was conducted using the Capacity Requirement Planning (CRP) method. Results and Discussion, comparison of available capacity and required capacity (load) are as follows, work station jaw crusher available capacity 36.74 hours/week while required capacity (load) 36 hours/week, work station bucket elevator available capacity 36, 74 hours/week while the required capacity (load) is 14.4 hours/week, work station ball mill available capacity is 36.74 hours/week while the required capacity (load) is 45.6 hours/week, and work station silo flour the available capacity is 36.74 hours/week while the required capacity (load) is 51.59 hours/week. In conclusion, two stations experience excess capacity, namely the jaw crusher work station with an excess capacity of 0.74 hours/week and the bucket elevator work station with an excess capacity of 22.34 hours/week. The other two work stations experienced a lack of capacity, namely the ball mill work station with a capacity shortage of 22.34 hours/week and the silo flour work station with a capacity shortage of 14.85 hours/week. Efforts to balance capacity by scheduling overtime and adding equipment (machinery) to work centers that lack capacity, so that the company's production targets are achieved.

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“…[ [15][16][17] measures of standard nervousness (max, mean, percentage and number of changes) are not horizon dependent. The mathematics of this step was elaborated in [18].…”

Section: Exploration and Quantificationmentioning

confidence: 99%

Tool for Nervousness Analysis in a Rolling Planning Environment via Historical Data

Lamothe¹

2021

Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems

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This paper analyses the modifications of plans exchanged between supply chain actors in a tactical planning rolling horizon process. A particular focus is on the changes of planned quantities in order to respond to fluctuating demand or to adapt to internal contingencies of the organization. They create instability and nervousness in the planning system. This paper presents a data-driven study to compare the behavior of planning decision makers in a context of certain and uncertain demand. We show through simulation and statistical analysis the effect of decision characteristics of one actor on the system nervousness and the resulting uncertainty for the other actors.

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A reactive decision-making approach to reduce instability in a master production schedule

Cited by 28 publications

References 33 publications

Analysis of production planning in a global manufacturing company with process mining

Analysis of production planning in a global manufacturing company with process mining

Production Capacity Requirements Planning Using The Capacity Method Requirement Planning

Tool for Nervousness Analysis in a Rolling Planning Environment via Historical Data

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