Aspects of the design and operation of production control systems in manufacturing industry

Computerised production control developments have concentrated on Manufacturing Resources Planning (MRP II) systems. The literature suggests however, that despite the massive investment in hardware, software and management education, successful implementation of such systems in manufacturing industries has proved difficult. This thesis reviews the development of production planning and control systems, in particular, investigates the causes of failures in implementing MRP/MRP II systems in industrial environments and argues that the centralised and top-down planning structure, as well as the routine operational methodology of such systems, is inherently prone to failure. The thesis reviews the control benefits of cellular manufacturing systems but concludes that in more dynamic manufacturing environments, techniques such as Kanban are inappropriate. The basic shortcomings of MRP II systems are highlighted and a new enhanced operational methodology based on distributed planning and control principles is introduced. Distributed Manufacturing Resources Planning (DMRP), was developed as a capacity sensitive production planning and control solution for cellular manufacturing environments. The system utilises cell based, independently operated MRP II systems, integrated into a plant-wide control system through a Local Area Network. The potential benefits of adopting the system in industrial environments is discussed and the results of computer simulation experiments to compare the performance of the DMRP system against the conventional MRP II systems presented. DMRP methodology is shown to offer significant potential advantages which include ease of implementation, cost effectiveness, capacity sensitivity, shorter manufacturing lead times, lower working in progress levels and improved customer service.

Cost effectiveness of production control systems

This thesis deals with the problems associated with the planning and control of production, with particular reference to a small aluminium die casting company. The main problem areas were identified as: (a) A need to be able to forecast the customers demands upon the company's facilities. (b) A need to produce a manufacturing programme in which the output of the foundry (or die casting section) was balanced with the available capacity in the machine shop. (c) The need to ensure that the resultant system enabled the company's operating budget to have a reasonable chance of being achieved. At the commencement of the research work the major customers were members of the automobile industry and had their own system of forecasting, from which they issued manufacturing schedules to their component suppliers, The errors in the forecast were analysed and the distributions noted. Using these distributions the customer's forecast was capable of being modified to enable his final demand to be met with a known degree of confidence. Before a manufacturing programme could be developed the actual manufacturing system had to be reviewed and it was found that as with many small companies there was a remarkable lack of formal control and written data. Relevant data with regards to the component and the manufacturing process had therefore to be collected and analysed. The foundry process was fixed but the secondary machining operations were analysed by a technique similar to Component Flow Analysis and as a result the machines were arranged in a series of flow lines. A system of manual production control was proposed and for comparison, a local computer bureau was approached and a system proposed incorporating the production of additional management information. These systems are compared and the relative merits discussed and a proposal made for implementation.

Modelling manufacturing planning and control systems:the application of object-oriented principles and discrete-event simulation

Manufacturing planning and control systems are fundamental to the successful operations of a manufacturing organisation. 10 order to improve their business performance, significant investment is made by companies into planning and control systems; however, not all companies realise the benefits sought Many companies continue to suffer from high levels of inventory, shortages, obsolete parts, poor resource utilisation and poor delivery performance. This thesis argues that the fit between the planning and control system and the manufacturing organisation is a crucial element of success. The design of appropriate control systems is, therefore, important. The different approaches to the design of manufacturing planning and control systems are investigated. It is concluded that there is no provision within these design methodologies to properly assess the impact of a proposed design on the manufacturing facility. Consequently, an understanding of how a new (or modified) planning and control system will perform in the context of the complete manufacturing system is unlikely to be gained until after the system has been implemented and is running. There are many modelling techniques available, however discrete-event simulation is unique in its ability to model the complex dynamics inherent in manufacturing systems, of which the planning and control system is an integral component. The existing application of simulation to manufacturing control system issues is limited: although operational issues are addressed, application to the more fundamental design of control systems is rarely, if at all, considered. The lack of a suitable simulation-based modelling tool does not help matters. The requirements of a simulation tool capable of modelling a host of different planning and control systems is presented. It is argued that only through the application of object-oriented principles can these extensive requirements be achieved. This thesis reports on the development of an extensible class library called WBS/Control, which is based on object-oriented principles and discrete-event simulation. The functionality, both current and future, offered by WBS/Control means that different planning and control systems can be modelled: not only the more standard implementations but also hybrid systems and new designs. The flexibility implicit in the development of WBS/Control supports its application to design and operational issues. WBS/Control wholly integrates with an existing manufacturing simulator to provide a more complete modelling environment.

Design of a multi-processor control systems

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Comparison of a preferred and actual method of selecting and implementing computerised control systems in a manufacturing environment

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An investigation of management accounting control systems in the palm oil industry:a sociomaterial approach to practice change

The primary aim of this research is to understand what constitutes management accounting and control (MACs) practice and how these control processes are implicated in the day to day work practices and operations of the organisation. It also examines the changes that happen in MACs practices over time as multiple actors within organisational settings interact with each other. I adopt a distinctive practice theory approach (i.e. sociomateriality) and the concept of imbrication in this research to show that MACs practices emerge from the entanglement between human/social agency and material/technological agency within an organisation. Changes in the pattern of MACs practices happens in imbrication processes which are produced as the two agencies entangle. The theoretical approach employed in this research offers an interesting and valuable lens which seeks to reveal the depth of these interactions and uncover the way in which the social and material imbricate. The theoretical framework helps to reveal how these constructions impact on and produce modifications of MACs practices. The exploration of the control practices at different hierarchical levels (i.e. from the operational to middle management and senior level management) using the concept of imbrication process also maps the dynamic flow of controls from operational to top management and vice versa in the organisation. The empirical data which is the focus of this research has been gathered from a case study of an organisation involved in a large vertically integrated palm oil industry company in Malaysia specifically the refinery sector. The palm oil industry is a significant industry in Malaysia as it contributed an average of 4.5% of Malaysian Gross Domestic Product, over the period 1990 -2010. The Malaysian palm oil industry also has a significant presence in global food oil supply where it contributed 26% of the total oils and fats global trade in 2010. The case organisation is a significant contributor to the Malaysian palm oil industry. The research access has provided an interesting opportunity to explore the interactions between different groups of people and material/technology in a relatively heavy process food industry setting. My research examines how these interactions shape and are shaped by control practices in a dynamic cycle of imbrications over both short and medium time periods.

Enhancing the performance of intelligent control systems in the face of higher levels of complexity and uncertainty

Modern advances in technology have led to more complex manufacturing processes whose success centres on the ability to control these processes with a very high level of accuracy. Plant complexity inevitably leads to poor models that exhibit a high degree of parametric or functional uncertainty. The situation becomes even more complex if the plant to be controlled is characterised by a multivalued function or even if it exhibits a number of modes of behaviour during its operation. Since an intelligent controller is expected to operate and guarantee the best performance where complexity and uncertainty coexist and interact, control engineers and theorists have recently developed new control techniques under the framework of intelligent control to enhance the performance of the controller for more complex and uncertain plants. These techniques are based on incorporating model uncertainty. The newly developed control algorithms for incorporating model uncertainty are proven to give more accurate control results under uncertain conditions. In this paper, we survey some approaches that appear to be promising for enhancing the performance of intelligent control systems in the face of higher levels of complexity and uncertainty.

Control Systems with Constraints and Uncertain Initial Conditions

AMS subject classification: 49N55, 93B52, 93C15, 93C10, 26E25.

The Closed Loop Model by Regional Economics or How Big is the Ants’ Footprint?

The economy is communication between Man and Nature. It is an interaction-network between our outside and inside Nature, that is, the external Nature surrounding us and the internal nature expressing our human essence. Money is an institution of the society, an infrastructure that ensures division of labour, enables the flow of information and material between the participants. The concept of regional material and financial circular flow will be more important with the oncoming peak-oil and post-carbon era. We should describe in time the outlines of closed or semi-closed loops economy. The fundamentals of Input-Output will flourish once again; it could help us formulate the link between the efficiency and resiliency of a regional complex system.

Optimal control of affine connection control systems from the point of view of Lie algebroids

The purpose of this paper is to use the framework of Lie algebroids to study optimal control problems for affine connection control systems (ACCSs) on Lie groups. In this context, the equations for critical trajectories of the problem are geometrically characterized as a Hamiltonian vector field.

Controller system design using the coefficient diagram method

Coefficient diagram method is a controller design technique for linear time-invariant systems. This design procedure occurs into two different domains: an algebraic and a graphical. The former is closely paired to a conventional pole placement method and the latter consists on a diagram whose reading from the plotted curves leads to insights regarding closed-loop control system time response, stability and robustness. The controller structure has two degrees of freedom and the design process leads to both low overshoot closed-loop time response and good robustness performance regarding mismatches between the real system and the design model. This article presents an overview on this design method. In order to make more transparent the presented theoretical concepts, examples in Matlab®code are provided. The included code illustrates both the algebraic and the graphical nature of the coefficient diagram design method. © 2016, King Fahd University of Petroleum & Minerals.

MILITARY VEHICLE OPTIMIZATION AND CONTROL

It is remarkable that there are no deployed military hybrid vehicles since battlefield fuel is approximately 100 times the cost of civilian fuel. In the commercial marketplace, where fuel prices are much lower, electric hybrid vehicles have become increasingly common due to their increased fuel efficiency and the associated operating cost benefit. An absence of military hybrid vehicles is not due to a lack of investment in research and development, but rather because applying hybrid vehicle architectures to a military application has unique challenges. These challenges include inconsistent duty cycles for propulsion requirements and the absence of methods to look at vehicle energy in a holistic sense. This dissertation provides a remedy to these challenges by presenting a method to quantify the benefits of a military hybrid vehicle by regarding that vehicle as a microgrid. This innovative concept allowed for the creation of an expandable multiple input numerical optimization method that was implemented for both real-time control and system design optimization. An example of each of these implementations was presented. Optimization in the loop using this new method was compared to a traditional closed loop control system and proved to be more fuel efficient. System design optimization using this method successfully illustrated battery size optimization by iterating through various electric duty cycles. By utilizing this new multiple input numerical optimization method, a holistic view of duty cycle synthesis, vehicle energy use, and vehicle design optimization can be achieved.