Integrated feedstock optimisation for multi-product polymer production

Thesis (PhD)--Stellenbosch University, 2022.ENGLISH ABSTRACT: A chemical complex can have multiple value chains, some of which may span across geographical locations. Decisions regarding the distribution of feedstock and intermediate feedstock to different production units can occur at different time intervals. This is highlighted as two problems, a feedstock distribution problem and an intermediate feedstock distribution problem. Unexpected events can cause an imbalanced value chain which requires timely decision-making to mitigate further adverse consequences. Scheduling methods can provide decision support during such events. The purpose of this research study is to develop an integrated decision support system which handles the two problems as a single problem and maximises profit in the value chain for hourly and daily decision-making. A high-level DSS architecture is presented that incorporates metaheuristic algorithms to generate production schedules for distribution of feedstock through the value chain. The solution evaluation process contains a balancing period to enable the application of metaheuristics to this type of problem and a novel encoding scheme is proposed for the hourly interval problem. It was found that metaheuristics algorithms can be used for this problem and integrated into the proposed decision support system.AFRIKAANSE OPSOMMING: ’n Chemiese kompleks kan verskeie waardekettings hê, waarvan sommige oor geografiese gebiede strek. Besluite rakende die verspreiding van grondstowwe en intermediêre grondstowwe na verskillende produksie-eenhede kan op verskillende tydsintervalle plaasvind. Dit word uitgelig as twee probleme: ’n probleem met die verspreiding van grondstowwe en ’n intermediêre grondstowwe verspreidingsprobleem. Onverwagte gebeure kan ’n ongebalanseerde waardeketting veroorsaak wat tydige besluitneming benodig om verdere gevolge te versag. Beplanningsmetodes kan ondersteuning bied tydens sulke geleenthede. Die doel van hierdie navorsingstudie was om ’n geïntegreerde stelsel vir besluitnemingsondersteuning oor die twee probleme as een probleem te ontwikkel, wat wins in die waardeketting vir uurlikse en daaglikse besluitneming maksimeer. ’n Hoëvlak DSS-argitektuur word aangebied met metaheuristieke om produksieskedules vir verspreidingstowwe deur die waardeketting te genereer. Die oplossingsevalueringsproses bevat ’n balanseerperiode om die metaheuristiek op hierdie tipe probleme toe te pas, en ’n nuwe koderingskema word voorgestel vir die uurlikse intervalprobleem. Die gevolgtrekking word gemaak dat metaheuristieke vir hierdie probleem gebruik kan word en ge¨ıntegreer kan word in die voorgestelde ondersteuningsstelsel vir besluitneming.Doctora

Application of metaheuristics in multi-product polymer production scheduling: A case study

Chemical manufacturers produce a range of polymer product families on a large scale within complex and dispersed manufacturing plants. These plants are connected through pipelines and are highly dependent on each other. Such a group of connected plants is referred to as a value chain. The process involves the continuous flow of raw materials known as feedstock, from one plant to another, enabling the continuous production of polymers. When the flow of feedstock through the value chain is interrupted due to unexpected events or planned maintenance at a plant, it results in irreversible losses. Consequently, prompt decision support is required to manage these disruptions and ensure the continuity of the flow. This paper evaluates several metaheuristics for effectively scheduling the flow between the plants within the value chain of a chemical manufacturer. These metaheuristics aim to provide near-optimal solutions after disrupting events occur and for the scheduling of periodic production. Sixteen diverse algorithms were considered – including greedy search, tabu search, simulated annealing, and the genetic algorithm – for the profitability of new schedules in the shortest computational time after flow interruption. Moreover, subject-matter experts tested and evaluated several scenario disturbances in the value chain process. The genetic algorithm and variations like local search, tabu search, and greedy search produced the best results. The contribution of this study includes evidence to show that inter-plant scheduling in a multi-product polymer production chain can be done within a reasonable time to ensure continuous process flow. In addition, a novel encoding scheme of decision variables is presented, allowing for scheduling over short or longer time horizons. Finally, the study shows that the performance results of the metaheuristics can guide practitioners on which to select for future implementation; this study showed that the genetic algorithm with population sizes of 50 to 120 and more than 100 generations proved to be best, while results can be obtained in less than 10 minutes