Model approximation for batch flow shop scheduling with fixed batch sizes

Batch flow shops model systems that process a variety of job types using a fixed infrastructure. This model has applications in several areas including chemical manufacturing, building construction, and assembly lines. Since the throughput of such systems depends, often strongly, on the sequence in which they produce various products, scheduling these systems becomes a problem with very practical consequences. Nevertheless, optimally scheduling these systems is NP-complete. This paper demonstrates that batch flow shops can be represented as a particular kind of heap model in the max-plus algebra. These models are shown to belong to a special class of linear systems that are globally stable over finite input sequences, indicating that information about past states is forgotten in finite time. This fact motivates a new solution method to the scheduling problem by optimally solving scheduling problems on finite-memory approximations of the original system. Error in solutions for these “t-step” approximations is bounded and monotonically improving with increasing model complexity, eventually becoming zero when the complexity of the approximation reaches the complexity of the original system.United States. Department of Homeland Security. Science and Technology Directorate (Contract HSHQDC-13-C-B0052)United States. Air Force Research Laboratory (Contract FA8750-09-2-0219)ATK Thiokol Inc

Optimal synthesis of storageless batch plants using the process intermediate storage operational policy

A novel operational policy, the Process Intermediate Storage (PIS) operational policy, is introduced and used to synthesize, schedule and design multipurpose batch plants. The model is based on the State Sequence Network (SSN) and non-uniform discretization of the time horizon of interest model developed by Majozi&Zhu (2001). Two cases are studied to determine the effectiveness of the operational policy. A plant without dedicated intermediate storage is considered in the first case. In this case the throughput is maximized with and without the use of the PIS operational policy. The use of the PIS operational policy results in a 50% improvement in the throughout. The second case is used to determine the minimum amount of intermediate storage while maintaining the throughput achieved with infinite intermediate storage. This resulted in a 33% reduction in the amount of dedicated intermediate storage. The models developed for both cases are MILP models. A design model is then developed to exploit the attributes of the PIS operational policy. The design model is a MINLP due to the capital cost objective function. This model is applied to a literature example and an industrial case study and in both cases results in improved flowsheets and reduced capital cost.Dissertation (MEng)--University of Pretoria, 2008.Chemical Engineeringunrestricte

Study on application possibilities of Case-Based Reasoning on the domain of scheduling problems

Ces travaux concernent la mise en place d'un système d'aide à la décision, s'appuyant sur le raisonnement à partir de cas, pour la modélisation et la résolution des problèmes d'ordonnancement en génie des procédés. Une analyse de co-citation a été exécutée afin d'extraire de la littérature la connaissance nécessaire à la construction de la stratégie d'aide à la décision et d'obtenir une image de la situation, de l'évolution et de l'intensité de la recherche du domaine des problèmes d'ordonnancement. Un système de classification a été proposée, et la nomenclature proposée par Blazewicz et al. (2007) a été étendue de manière à pouvoir caractériser de manière complète les problèmes d'ordonnancement et leur mode de résolution. Les difficultés d'adaptation du modèle ont été discutées, et l'efficacité des quatre modèles de littérature a été comparée sur trois exemples de flow-shop. Une stratégie de résolution est proposée en fonction des caractéristiques du problème mathématique. ABSTRACT : The purpose of this study is to work out the foundations of a decision-support system in order to advise efficient resolution strategies for scheduling problems in process engineering. This decision-support system is based on Case-Based Reasoning. A bibliographic study based on co-citation analysis has been performed in order to extract knowledge from the literature and obtain a landscape about scheduling research, its intensity and evolution. An open classification scheme has been proposed to scheduling problems, mathematical models and solving methods. A notation scheme corresponding to the classification has been elaborated based on the nomenclature proposed by Blazewicz et al. (2007). The difficulties arising during the adaptation of a mathematical model to different problems is discussed, and the performances of four literature mathematical models have been compared on three flow-shop examples. A resolution strategy is proposed based on the characteristics of the scheduling problem

Investigating Different Types of Variability in Food Production System

A high level of competition in the food industry, specifically in the Middle East and the UK has forced companies to improve their processes by reducing lead time, waste, and costs and increasing production efficiency. The main challenge to the achievement of the process improvement objectives is the high level of process variability. Therefore, this research investigates the different types of variability in food production system and proposes a methodology to reduce the effect variability in food production system. The variability can be caused by several factors, for instance, in biscuit production lines variability can be induced due to short breakdown and long breakdown, variable processing times, variable temperature, etc. The proposed approach addresses process time variability issues associated with both make-to-stock (MTS) and make-to-order (MTO) manufacturing environments using an iterated approach. The proposed methodology integrates process mapping, (which is a lean tool for identifying value added and non-value added activities), discrete event simulation (to mirror the real production line), Taguchi orthogonal arrays (to generate different scenarios in order to investigate the effect of variability on the simulation model), correlation analysis (to identify the highest variability factors), and the rule based system (to improve food production system performance based on identified key performance indicators (KPIs)). The research uses a biscuit production line as a case study to validate the proposed methodology. The application of the proposed approach determines that the highest effected KPI is %working. The results showed that after implementation of the rule-based system, key performance improved in high variable areas. Results analysis based on before scenario shows that %working performance indicator is highly effected by variable temperature, speed, and breakdown factors for high variable areas such as baking, cooling, aligning, and packing. Based on identified factors and high variable areas, rules are developed by applying standardisation setting (SOP, WI, PP) in high variable areas and the results shows %working improved in baking by 4.78%, in cooling by 16.06%, in aligning by 0.35%, in packing machine1 by 2.5%, in packing machine2 by 2.37%, in packaging1 by 3.35%, and in packaging2 by 3.16%. The integrated method allow quick response , control the environment without production interruption, reduce number of experiments , and reducing variability in high variable areas, which narrowed the improvement in the required areas and increased its effectiveness

Planning and scheduling in pharmaceutical supply chains

Ph.DDOCTOR OF PHILOSOPH