Real-time production scheduling in a multi-grade PET resin plant under demand uncertainty

Hatzikonstantinou, Olympia; Athanasiou, Efstratios; Pandelis, Dimitrios G.

doi:10.1016/j.compchemeng.2012.01.011

Cited by 3 publications

(2 citation statements)

References 33 publications

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“…Optimization of production in bottle grade PET resin plant is target of model considered in this study. Some of the recent studies on bottle grade PET resin are given in Liberopoulos et al (2010) and in Hatzikonstantinou et al (2012). Production scheduling of a PET resin plant according to defined quality range is argued on these articles.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the Production Planning Policy Alternatives in a Pet Resin Production Plant: a Case Study From Turkey

Demirkan

Durmuşoğlu²

2020

BJO&PM

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Goal: The main purpose of this work is to develop several production planning models for one of bottle grade PET production plants (in Turkey) under different scenarios by considering different levels of inventory (no stock and different levels of safety stocks), different energy sourcing alternatives (natural gas/coal or both) and production throughput (different lot sizes). Design/Methodology/Approach: Deterministic multi-product multi-period single level mixed integer linear programming model is presented. The model is implemented for the above defined scenarios. We have also considered the total emission produced for different energy alternatives. Results: The models for the different scenarios have shown that significant performance improvements can be achieved by changing the parameters/policies of the production. The best model obtained has yielded 6.6% of profit improvement and 6.9% of cost reduction. Limitations of the investigation: Planning horizon of this work could cover the data of years 2014 to 2018. However, the actual data employed for this study is limited with one year due to unavailability of further data. In addition to this, improvement of current production planning approach of the plant by implementation of proposed model is one of the objectives of this study to see success rate of model. Though, this couldn’t be realized. We hypothetically tested the improvement provided by the proposed model, therefore we can’t analyze the actual improvement. Practical implications: Interactions among optimal results obtained by running model with different scenarios and their effect on selected performance variables are the main contribution of this work. Similar methodology could be used at other PET resin manufacturing plants or alternatively the production facilities having similar type of continuous manufacturing processes to find their optimal levels of inventory, production throughput and proper choice for energy sourcing alternative. Originality/Value: The research on the production planning for PET resin industry by considering the different scenarios (levels of inventory / energy sourcing alternatives/ production throughput) is novel as far as we know, and therefore the approach used in this study is expected to be useful for other similar plants.

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Section: Introductionmentioning

confidence: 99%

Evaluation of the Production Planning Policy Alternatives in a Pet Resin Production Plant: a Case Study From Turkey

Demirkan

Durmuşoğlu²

2020

BJO&PM

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“…Another challenging issue is to investigate the ways of controlling a large number of uncertain parameters. Hence, scheduling under uncertainty has received a lot of attention in recent years (e.g., Hatzikonstantinou et al 2012;Vargas and Metters 2011;Torabi et al 2010;Verderame and Floudas 2009). Uncertainty can be derived from many aspects, such as demand or product orders, alternation or priority of orders, equipment failures, resource changes, and processing time variability.…”

Section: Literature Reviewmentioning

confidence: 99%

An application of principal component analysis and logistic regression to facilitate production scheduling decision support system: an automotive industry case

Saeed

Bashiri

2013

J Ind Eng Int

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Production planning and control (PPC) systems have to deal with rising complexity and dynamics. The complexity of planning tasks is due to some existing multiple variables and dynamic factors derived from uncertainties surrounding the PPC. Although literatures on exact scheduling algorithms, simulation approaches, and heuristic methods are extensive in production planning, they seem to be inefficient because of daily fluctuations in real factories. Decision support systems can provide productive tools for production planners to offer a feasible and prompt decision in effective and robust production planning. In this paper, we propose a robust decision support tool for detailed production planning based on statistical multivariate method including principal component analysis and logistic regression. The proposed approach has been used in a real case in Iranian automotive industry. In the presence of existing multisource uncertainties, the results of applying the proposed method in the selected case show that the accuracy of daily production planning increases in comparison with the existing method.

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Empirical Researches (Based on SEM) on the Factors that Affect Manufacturing Performance

Liu

2013

International Asia Conference on Industrial Engineering and Management Innovation (IEMI2012) Proceedings

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Real-time production scheduling in a multi-grade PET resin plant under demand uncertainty

Cited by 3 publications

References 33 publications

Evaluation of the Production Planning Policy Alternatives in a Pet Resin Production Plant: a Case Study From Turkey

Evaluation of the Production Planning Policy Alternatives in a Pet Resin Production Plant: a Case Study From Turkey

An application of principal component analysis and logistic regression to facilitate production scheduling decision support system: an automotive industry case

Empirical Researches (Based on SEM) on the Factors that Affect Manufacturing Performance

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