Multi-party risk management helps manage cement plant construction in Thailand

Several parties (stakeholders) are involved in a construction project. The conventional Risk Management Process (RMP) manages risks from a single party perspective, which does not give adequate consideration to the needs of others. The objective of multi-party risk management is to assist decision-makers in managing risk systematically and most efficiently in a multi-party environment. Multi-party Risk Management Processes (MRMP) consist of risk identification, structuring, analysis and developing responses from all party perspectives. The MRMP has been applied to a cement plant construction project in Thailand to demonstrate its effectiveness.

Multi-valued control problems and mixture density network

We have proposed a novel robust inversion-based neurocontroller that searches for the optimal control law by sampling from the estimated Gaussian distribution of the inverse plant model. However, for problems involving the prediction of continuous variables, a Gaussian model approximation provides only a very limited description of the properties of the inverse model. This is usually the case for problems in which the mapping to be learned is multi-valued or involves hysteritic transfer characteristics. This often arises in the solution of inverse plant models. In order to obtain a complete description of the inverse model, a more general multicomponent distributions must be modeled. In this paper we test whether our proposed sampling approach can be used when considering an arbitrary conditional probability distributions. These arbitrary distributions will be modeled by a mixture density network. Importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The effectiveness of the importance sampling from an arbitrary conditional probability distribution will be demonstrated using a simple single input single output static nonlinear system with hysteretic characteristics in the inverse plant model.

Osmotic dehydration in plant tissues

The primary aim of the thesis is to provide a comprehensive investigation of the osmotic dehydration processes in plant tissue. Effort has been concentrated on the modelling for simulating the processes. Two mathematical models for simulating the mass transfer during osmotic dehydration processes in plant tissues are developed and verified using existing experimental data. Both models are based on the mechanism of diffusion and convection of any mobile material that can transport in plant tissues. The mass balance equation for the transport of each constituent is established separately for intracellular and extra-cellular volumes with taking into account the mass transfer across the cell membrane the intracellular and extra-cellular volumes and the shrinkage of the whole tissue. The contribution from turgor pressure is considered in both models. Model two uses Darcy’s law to build the relation between shrinkage velocity and hydrostatic pressure in each volume because the plant tissue can be considered as the porous medium. Moreover, it has been extended to solve the multi-dimensional problems. A lot of efforts have been made to the parameter study and the sensitivity analyses. The parameters investigated including the concentration of the osmotic solution, diffusion coefficient, permeability of the cell membrane, elastic modulus of the cell wall, critical cell volume etc. The models allow us to quantitatively simulate the time evolution of intracellular and extra-cellular volumes as well as the time evolution of concentrations in each cross-section.

Integrated manufacturing systems design in a multi-product company

Using a hydraulic equipment manufacturing plant as the case study, this work explores the problems of systems integration in manufacturing systems design, stressing the behavioural aspects of motivation and participation, and the constraints involved in the proper consideration of the human sub-system. The need for a simple manageable modular organisation structure is illustrated, where it is shown, by reference to systems theory, how a business can be split into semi-autonomous operating units. The theme is the development of a manufacturing system based on an analysis of the business, its market, product, technology and constraints, coupled with a critical survey of modern management literature to develop an integrated systems design to suit a specific company in the current social environment. Society currently moves through a socio-technical revolution with man seeking higher levels of motivation. The transitory environment from an autocratic/paternalistic to a participative operating mode demands systems parameters only found to a limited extent in manufacturing systems today. It is claimed, that modern manufacturing systems design needs to be based on group working, job enrichment, delegation of decision making and reduced job monotony. The analysis shows how negative aspects of cellular manufacture such as lack of flexibility and poor fixed asset utilisation are relatively irrelevant and misleading in the broader context of the need to come to terms with the social stresses imposed on a company operating in the industrial environment of the present and the immediate future.

Performance, emission and combustion characteristics of an indirect injection (IDI) multi-cylinder compression ignition (CI) engine operating on neat jatropha and karanj oils preheated by jacket water

Renewable non-edible plant oils such as jatropha and karanj have potential to substitute fossil diesel fuels in CI engines. A multi-cylinder water cooled IDI type CI engine has been tested with jatropha and karanj oils and comparisons made against fossil diesel. The physical and chemical properties of the three fuels were measured to investigate the suitability of jatropha and karanj oils as fuels for CI engines. The engine cooling water circuit and fuel supply systems were modified such that hot jacket water preheated the neat plant oil prior to injection. Between jatropha and karanj there was little difference in the performance, emission and combustion results. Compared to fossil diesel, the brake specific fuel consumption on volume basis was around 3% higher for the plant oils and the brake thermal efficiency was almost similar. Jatropha and karanj operation resulted in higher CO 2 and NO x emissions by 7% and 8% respectively, as compared to diesel. The cylinder gas pressure diagram showed stable engine operation with both plant oils. At full load, the plant oils gave around 3% higher peak cylinder pressure than fossil diesel. With the plant oils, cumulative heat release was smaller at low load and almost similar at full load, compared to diesel. At full load, the plant oils exhibited 5% shorter combustion duration. The study concludes that the IDI type CI engine can be efficiently operated with neat jatropha (or karanj) oil preheated by jacket water, after small modifications of the engine cooling and fuel supply circuits. © 2012 Elsevier Ltd.

A decision support system for supplier selection and order allocation in stochastic, multi-stakeholder and multi-criteria environments

Integrated supplier selection and order allocation is an important decision for both designing and operating supply chains. This decision is often influenced by the concerned stakeholders, suppliers, plant operators and customers in different tiers. As firms continue to seek competitive advantage through supply chain design and operations they aim to create optimized supply chains. This calls for on one hand consideration of multiple conflicting criteria and on the other hand consideration of uncertainties of demand and supply. Although there are studies on supplier selection using advanced mathematical models to cover a stochastic approach, multiple criteria decision making techniques and multiple stakeholder requirements separately, according to authors' knowledge there is no work that integrates these three aspects in a common framework. This paper proposes an integrated method for dealing with such problems using a combined Analytic Hierarchy Process-Quality Function Deployment (AHP-QFD) and chance constrained optimization algorithm approach that selects appropriate suppliers and allocates orders optimally between them. The effectiveness of the proposed decision support system has been demonstrated through application and validation in the bioenergy industry.