The impact of uncertain yield on capacity acquisition in process plant networks

In this paper, we consider the case of process plant networks, which consolidate production of components. It is well known that such networks take advantage of process commonalities thereby accruing economies of scale advantages. It has also been shown in recent work that besides scale economies, process plant networks also enjoy risk-pooling advantages which are a direct outcome of network structure. In this research, motivated by real-world examples, we study capacity acquisition in a process plant network when demand and process yield are both uncertain. We show that the optimal capacity acquired in such situations may be considerably higher or lower than that acquired when yield is assumed perfect. We develop distribution-free policies for optimal capacity acquisition. We illustrate our results by means of a numerical example and study the sensitivity to important model parameters. For specific distributional assumptions we also provide closed-form results for the optimal capacity acquisition. We consider our work as perhaps the first to bridge the gap between operational level quality control studies and strategic level network configuration research. Overall, we believe that this paper opens up several avenues for future research integrating these two important areas.     

Modelling and simulation of mobile jet agitator for a biogas plant

This work deals with the modeling and simulation of mixture process in a biogas plant. This mixing process involves a closed pumping procedure, which pumps the constituents of the biogas plant using jet agitators inside the tank. For this purpose, an experimental model has been designed and built in reduced scale to study the mixture process. Furthermore, this process has been simulated numerically. (© 2015 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Preventive maintenance scheduling of multi-cogeneration plants using integer programming

Maintenance scheduling of cogeneration plants, which produce both electric power and desalinated water, is a typical complex process with long-term operations and planning problems. The plants' maintenance scheduling process has to determine the appropriate schedule for preventive maintenance, while satisfying all the system constraints and maintaining adequate system availability. It is an optimization problem and the maintenance and system constraints include the crew constraint, maintenance window constraint and time limitation constraint. In this paper, an integer linear-programming model, which has been developed, is described which schedules the preventive maintenance tasks in a multi-cogeneration plant. Results of a test example of such a plant situated in Kuwait are presented to show the applicability of the approach.     

Linear Programming Applied to Production Planning and Operation of a Chemical Process

To employ linear programming in production-planning problems in the chemical industry it is often necessary to make a linear model of plant which seems highly non-linear. An approach with some generality is described that reasonably combines accuracy and economy.Next, the hierarchy of planning levels around a chemical plant is considered from investment planning through to process operation. This highlights difficulties, inherent in on-line computer optimizing proposals, that are often played down. In short, the considerations which have most influence on determining optimum operating conditions are shown to have little to do with the instantaneous state of the chemical process.Given that perfection is unattainable it is argued that in some cases the best way to run chemical plant is infrequent off-line optimization leading to plans whose feasibility is maintained in the short term with very little calculation if the right sort of linear process model exists.     

Analysis of the activated sludge model (number 1)

We analyse a model for the activated sludge process occurring in a biological reactor without recycle. The biochemical processes occurring within the reactor are represented by the activated sludge model number 1 (ASM1). In the past the ASM1 model has been investigated via direct integration of the governing equations. This approach is time-consuming as parameter regions of interest (in terms of the effluent quality leaving the plant) can only be determined through laborious and repetitive calculations. In this work we use continuation methods to determine the steady-state behaviour of the system. In particular, we determine bifurcation values of the residence time, corresponding to branch points, that are crucial in determining the performance of the plant.     

Developments in delay time analysis for modelling plant maintenance

Delay time (DT) analysis is a pragmatic mathematical concept readily embraced by engineers which has been developed as a means to model maintenance decision problems. Attention is focused upon the maintenance engineering decisions of what to do, as opposed to the logistical decisions of how to do it. This paper reviews the cumulative knowledge and experience of delay time modelling. The decision environment within which delay time (DT) models are intended as decision aids is briefly reviewed, and the initial development of simple DT models for a repairable component and a complex plant presented. Variations on the basic model are outlined and discussed including perfect and non-perfect inspection, steady state and non-steady state conditions, and homogeneous and non-homogeneous Poisson arrival rate of defects. Attention is given to the parameter estimation process, and both subjective and objective estimation techniques are outlined. Case sketches present practical experience in using the DT concept to model actual plant, to assess the benefits obtained, and to validate modelling and parameter assessment.     

Scheduling continuous casting of aluminum using a multiple objective ant colony optimization metaheuristic

This paper presents an ant colony optimization metaheuristic for the solution of an industrial scheduling problem in an aluminum casting center. We present an efficient representation of a continuous horizontal casting process which takes account of a number of objectives that are important to the scheduler. We have incorporated the methods proposed in software that has been implemented in the plant.     

An approach to modelling industrial unit processes: application to a spiral concentrator for minerals

A suite of computer models which simulate process operations in common use in the minerals processing industry is being developed. Application of the models is described with reference to a particular process device, the spiral concentrator. The paper sets out to explain the basic strategy behind the unit process modelling approach and discusses in detail the overall model structure adopted. The model aims to provide a set of equations, with sufficient physical significance to give a reasonable fit to any specific data set, and which can be systematically adjusted (through auxiliary models, user judgement and experience) to provide meaningful performance predictions over a broad range of operating conditions. The approach is thought to be applicable to a wide variety of processes. The model has been tested using a variety of ores, separated on plant-scale equipment and practical examples are given. The scope and limitations of the method are reported, drawing on the results of parallel experimental work. The extent to which this kind of approach can be used as a predictive tool in process design applications and in the day-to-day running of mineral processing plant is discussed.     

Heuristic Interpretation of Infeasible Solutions to a Production Scheduling Problem in Cigarette Manufacture

In this paper an end-user Infeasibility Resolution Heuristic (IRH) is developed to assist managers and production schedulers in the evaluation and interpretation of infeasible solutions arising from the use of a production scheduling model of a tobacco processing plant. The primary aim of the model is initially to determine whether the forecast annual demand for tobacco products can be met by the plant, and if not what must be done. Having determined that the demanded quantities are feasible, the model is then used to arrive at a production schedule such that the minimum number of machines are used in the entire process for the planning period (the model is a monthly one linked together by the closing stock equations for up to 12 months ahead). The operations of the plant modelled include the selection of the appropriate blend of leaf, assignment of the forecast product demand to suitable making machines, production of the required quantity of filters, assignment of the cigarettes produced to specific packers and then the determination as to whether the final product produced in the current period will be used to satisfy the current month's demand or demand in the future. The problem of sequencing the monthly production once the production schedule is determined has not been dealt with in this paper.     

Modelling a product-mix determination problem

This study presents a combined linear programming package and a user-oriented program for its data input employed in product-mix determination. An optimal product-mix is to be determined for a rapidly changing manufacturing environment. The study consists of developing an interactive computer program for the solution of a product-mix problem. The user-oriented program has been developed so that a person familiar with the plant can determine the ‘best’ mix which should be produced. This study provides a quantitative tool to aid in the decision-making process when time is limited and the production process dynamic.     

Evaluating the information content of a measure of plant output: An application to high-technology manufacturing

Commonly used measures of plant output have been criticized for their inability to provide information required to manage the dynamic operations of high-technology manufacturing plants. In this paper, we propose tests to evaluate the information content of a measure of plant output that is specifically directed at these issues. These tests are based on recent developments in DATA Envelopment Analysis (DEA), namely the Cone Ratio Envelopments. In this new application of DEA models, we shift the focus from Decision Making Units (DMUs) being evaluated to the DMUs that are being used to effect evaluations. The proposed tests are applied to evaluate the information contnet of a complexity adjusted measure of plant output, which we refer to as Total Net Die Equivalent (TNDE). Developed recently in the context of a high-technology manufacturing plant—a wafer fabrication plant of a merchant semiconductor manufacturing company-TNDE reflects the ongoing changes in product and process technologies, process flow characteristics, and volume of production. Evaluating the information content on joint criteria of recency and efficiency, the results of our tests, conducted over a 28-month period in the wafer fabrication plant,show that TNDE as a single aggregate (scalar) measure of plant output outperforms the two outputs from which it is synthesized. Thus, TNDE as a single measure of output can be used to provide an improved basis for planning a plant's future operations. En route to the development and application of the proposed tests, we illustrate how DEA concepts and models provide a rigorous and systematic basis for conducting ex post technology evaluation to guide continuous improvements in a plant's current operations.     

Modelling supervisory control systems using fuzzy cognitive maps

Modelling complex systems and their supervisior has attracted the high interest of many scientists and engineers. There has been a need for highly sophisticated Autonomous Intelligent Systems. A very promising methodology to model the Supervisor of a plant is the use of Fuzzy Cognitive Maps (FCM). FCM are a combination of Fuzzy Logic and Neural Networks. A new mathematical model for FCMs is proposed and its representation is examined in this paper. FCM construction is presented through the development of the model for a simple control process problem. Then, issues for the application of FCM as the model of the supervisor of a complex system are addressed and a hierarchical two-level structure is proposed.     

The delay-time modelling of preventive maintenance of plant given limited PM data and Selective repair at PM

This paper presents a maintenance-modelling case study of aplant manufacturing brake linings. A delay–time modelis developed and applied to model and optimize preventive maintenance(PM). A key subsystem in the plant is used to illustrate themodelling process and management reaction. Defects identifiedat PM may not all be removed. This incomplete response to PMis a feature which has not been modelled before. The parametervalues of the delay-time process are estimated from objectivedata from maintenance records of failures, using the methodof maximum likelihood. This is aided by a theorem extendingresults on the NHPP arival rate of failures in a perfect-inspectioncase to the non-perfect-inspection case. Problems of parameterestimation given inadequate data collected at PMs are discussed,and the necessity to augment objective data with subjectiveassessments highlighted. Based upon the estimated model parametersand delay-time distribution, an inspection model is constructedto describe the relationship between the total unit downtimeand the PM interval. The response of management is discussed.     

Application of computer modelling to hygienic plant design

The aim of the food industry is to supply consumers with safe,high-quality, and wholesome products. Recent developments inthe industry, such as the elimination of preservatives, longerproduction runs, and frequent product changes, require a greaterattention to product safety at the design stage. This placesincreasing demands upon the design of process equipment, andhygienic plant design in particular, to ensure the safety ofproducts. This paper covers work carried out at Unilever Researchover the last five years aimed at developing suitable theoreticalmethods for investigating design and operational aspects forhygienic plant. Such a method requires three things for it to be of practicalbenefit: good physical insights, modern modelling techniques,and modern computing power. Since a wide range of food-processingoperations involve complex product flows, the core element ofthis approach has been the use of computational fluid dynamics(CFD), particularly the use of large commercial CFD codes. Moreover,the wide range of product rheologies encountered in the foodindustry has necessitated that these codes be flexible enoughto model the physics of both Newtonian and non-Newtonian fluids.Theresulting method should provide a valuable new tool to the hygienic-plantdesiener. The CFD approach has been used to investigate the interactionsbetween product rheology. heat transfer. mass transfer. andequipment geometry. In particular, it is shown that the interactionbetween product rheology and equipment geometry has a largeeffect on the resulting flow pattern. with significant consequencesfor hygienic plant design, namely that plant designed for oneproduct type may be unsuitable for use with others. This isillustrated by examples using dead-end and T-piece geometriesin process systems.     

Modelling maintenance practice of production plant using the delay-time concept

In this paper we present a study carried out for a copper productsmanufacturing company, developing and applying the delay-timemodelling technique to model and thus optimize preventive maintenance(PM) of the plant. A key machine in the plant is used to illustratethe modelling process and management reaction. The parameter values of the process by which faults arise andof the delay-time distribution are estimated from maintenancerecord data of failures and faults found at PM, using the methodof maximum likelihood. A test of the model fit to data is carriedout. Based upon the estimated model parameters and the failuredelay time, an inspection model is proposed to describe therelationship between the total downtime and the PM interval.     

A hybrid multi-objective evolutionary algorithm based on NSGA-II for practical scheduling with release times in steel plants

The hot metal is produced from the blast furnaces in the iron plant and should be processed as soon as possible in the subsequent steel plant for energy saving. Therefore, the release times of hot metal have an influence on the scheduling of a steel plant. In this paper, the scheduling problem with release times for steel plants is studied. The production objectives and constraints related to the release times are clarified, and a new multi-objective scheduling model is built. For the solving of the multi-objective optimization, a hybrid multi-objective evolutionary algorithm based on non-dominated sorting genetic algorithm-II (NSGA-II) is proposed. In the hybrid multi-objective algorithm, an efficient decoding heuristic (DH) and a non-dominated solution construction method (NSCM) are proposed based on the problem-specific characteristics. During the evolutionary process, individuals with different solutions may have a same chromosome because the NSCM constructs non-dominated solutions just based on the solution found by DH. Therefore, three operations in the original NSGA-II process are modified to avoid identical chromosomes in the evolutionary operations. Computational tests show that the proposed hybrid algorithm based on NSGA-II is feasible and effective for the multi-objective scheduling with release times.     

Priority planning of a dynamic complex product mix: Elements for a computerized interface between delivery times and plant utilization

The priority planning process is both the management of ensuring reliability in confirming delivery times and maximizing plant capacity utilization.A framework is presented for the decision process of order planning in a business environment with a dynamic product mix consisting of both standard and non-standard products and with a limited machine capacity.The concept of a computerized interface between the priority planning process and the confirmed order file is presented.A simulation study is done to determine the relationship between different manufacturing strategies, delivery time policies and plant efficiency. The method is applied to the production of engineering plastic materials.     

Optimum manpower models for a production system with varying production rates

A minimum number of workers is required for a particular operation on the main assembly line of a production system. Considering this constraint and the standards of operations for different work elements, norms for all tasks in the whole assembly process are fixed by the management. Based on these norms, some optimum models have been suggested for estimation of work force on the assembly line for different rates of production. The estimation for varying production rates is done with reference to the present production rate and to the maximum installed capacity of the plant by introducing the integer approximation. The optimum model helps the management to schedule a quick and economic production plan.     

Computational simulation of piezo-electrically stimulated bone remodeling surrounding teeth implant

Since the natural ligament responsible for the fixation of teeth in jawbone is destroyed when artificial replacements are implanted, the mechanical stimulation of the bone is reversed. Idea of this research project is the development of active implants which provide additional electrical stimulation for bone adaption. A new electromechanically driven bone remodeling theory will be developed and the osseointegration of bone implants has been simulated by means of bio-active interface theory. The thin bone-implant interface is described by the Drucker-Prager plasticity model. Besides the consistent combination of electromechanical bone remodeling simulation, 3D-finite element model of lower mandible has been reconstructed. As the micromotions at the implant-abutment level are reported to be a major determinant of longterm implant success, the osseointegration process is limited by micromotion threshold. The applicability is indicated on a dental implant in order to optimize new developed techniques for activating implants with piezo-electric coatings. (© 2015 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)