DECISION SUPPORT MODEL IN FAILURE-BASED COMPUTERIZED MAINTENANCE MANAGEMENT SYSTEM FOR SMALL AND MEDIUM INDUSTRIES

Maintenance decision support system is crucial to ensure maintainability and reliability of equipments in production lines. This thesis investigates a few decision support models to aid maintenance management activities in small and medium industries. In order to improve the reliability of resources in production lines, this study introduces a conceptual framework to be used in failure-based maintenance. Maintenance strategies are identified using the Decision-Making Grid model, based on two important factors, including the machines’ downtimes and their frequency of failures. The machines are categorized into three downtime criterions and frequency of failures, which are high, medium and low. This research derived a formula based on maintenance cost, to re-position the machines prior to Decision-Making Grid analysis. Subsequently, the formula on clustering analysis in the Decision-Making Grid model is improved to solve multiple-criteria problem. This research work also introduced a formula to estimate contractor’s response and repair time. The estimates are used as input parameters in the Analytical Hierarchy Process model. The decisions were synthesized using models based on the contractors’ technical skills such as experience in maintenance, skill to diagnose machines and ability to take prompt action during troubleshooting activities. Another important criteria considered in the Analytical Hierarchy Process is the business principles of the contractors, which includes the maintenance quality, tools, equipments and enthusiasm in problem-solving. The raw data collected through observation, interviews and surveys in the case studies to understand some risk factors in small and medium food processing industries. The risk factors are analysed with the Ishikawa Fishbone diagram to reveal delay time in machinery maintenance. The experimental studies are conducted using maintenance records in food processing industries. The Decision Making Grid model can detect the top ten worst production machines on the production lines. The Analytical Hierarchy Process model is used to rank the contractors and their best maintenance practice. This research recommends displaying the results on the production’s indicator boards and implements the strategies on the production shop floor. The proposed models can be used by decision makers to identify maintenance strategies and enhance competitiveness among contractors in failure-based maintenance. The models can be programmed as decision support sub-procedures in computerized maintenance management systems

An Agent Operationalization Approach for Context Specific Agent-Based Modeling

The potential of agent-based modeling (ABM) has been demonstrated in various research fields. However, three major concerns limit the full exploitation of ABM; (i) agents are too simple and behave unrealistically without any empirical basis, (ii) \'proof of concept\' applications are too theoretical and (iii) too much value placed on operational validity instead of conceptual validity. This paper presents an operationalization approach to determine the key system agents, their interaction, decision-making and behavior for context specific ABM, thus addressing the above-mentioned shortcomings. The approach is embedded in the framework of Giddens\' structuration theory and the structural agent analysis (SAA). The agents\' individual decision-making (i.e. reflected decisions) is operationalized by adapting the analytical hierarchy process (AHP). The approach is supported by empirical system knowledge, allowing us to test empirically the presumed decision-making and behavioral assumptions. The output is an array of sample agents with realistic (i.e. empirically quantified) decision-making and behavior. Results from a Swiss mineral construction material case study illustrate the information which can be derived by applying the proposed approach and demonstrate its practicability for context specific agent-based model development.Agent Operationalization, Decision-Making, Analytical Hierarchy Process (AHP), Agent-Based Modeling, Conceptual Validation

Training materials for different categories of users

Agricultural and Food Policy, Environmental Economics and Policy, Farm Management, Land Economics/Use, Production Economics, Teaching/Communication/Extension/Profession,

A computer adaptive measure of delay discounting

Delay discounting has been linked to important behavioral, health, and social outcomes, including academic achievement, social functioning and substance use, but thoroughly measuring delay discounting is tedious and time consuming. We develop and consistently validate an efficient and psychometrically sound computer adaptive measure of discounting. First, we develop a binary search–type algorithm to measure discounting using a large international data set of 4,190 participants. Using six independent samples ($N$ = 1,550), we then present evidence of concurrent validity with two standard measures of discounting and a measure of discounting real rewards, convergent validity with addictive behavior, impulsivity, personality, survival probability; and divergent validity with time perspective, life satisfaction, age and gender. The new measure is considerably shorter than standard questionnaires, includes a range of time delays, can be applied to multiple reward magnitudes, shows excellent concurrent, convergent, divergent, and discriminant validity—by showing more sensitivity to effects of smoking behavior on discounting.Nehru Trust for Cambridge University, Cambridge Overseas Trus

Computer-based tools for supporting forest management. The experience and the expertise world-wide

Report of Cost Action FP 0804 Forest Management Decision Support Systems (FORSYS)Computer-based tools for supporting forest management. The experience and the expertise world-wide answers a call from both the research and the professional communities for a synthesis of current knowledge about the use of computerized tools in forest management planning. According to the aims of the Forest Management Decision Support Systems (FORSYS) (http://fp0804.emu.ee/) this synthesis is a critical success factor to develop a comprehensive quality reference for forest management decision support systems. The emphasis of the book is on identifying and assessing the support provided by computerized tools to enhance forest management planning in real-world contexts. The book thus identifies the management planning problems that prevail world-wide to discuss the architecture and the components of the tools used to address them. Of importance is the report of architecture approaches, models and methods, knowledge management and participatory planning techniques used to address specific management planning problems. We think that this synthesis may provide effective support to research and outreach activities that focus on the development of forest management decision support systems. It may contribute further to support forest managers when defining the requirements for a tool that best meets their needs. The first chapter of the book provides an introduction to the use of decision support systems in the forest sector and lays out the FORSYS framework for reporting the experience and expertise acquired in each country. Emphasis is on the FORSYS ontology to facilitate the sharing of experiences needed to characterize and evaluate the use of computerized tools when addressing forest management planning problems. The twenty six country reports share a structure designed to underline a problem-centric focus. Specifically, they all start with the identification of the management planning problems that are prevalent in the country and they move on to the characterization and assessment of the computerized tools used to address them. The reports were led by researchers with background and expertise in areas that range from ecological modeling to forest modeling, management planning and information and communication technology development. They benefited from the input provided by forest practitioners and by organizations that are responsible for developing and implementing forest management plans. A conclusions chapter highlights the success of bringing together such a wide range of disciplines and perspectives. This book benefited from voluntary contributions by 94 authors and from the involvement of several forest stakeholders from twenty six countries in Europe, North and South America, Africa and Asia over a three-year period. We, the chair of FORSYS and the editorial committee of the publication, acknowledge and thank for the valuable contributions from all authors, editors, stakeholders and FORSYS actors involved in this project

A Quantisation of Cognitive Learning Process by Computer Graphics-Games: Towards More Efficient Learning Models

Research group of Computer Sciences at DMU, Psychology Research Group at University of Birmingham and Reseach Group of Computer Science at University of Northumbria.With the latest developments in computer technologies and artificial intelligence (AI) techniques, more opportunities of cognitive data acquisition and stimulation via game-based systems have become available for computer scientists and psychologists. This may lead to more efficient cognitive learning model developments to be used in different fields of cognitive psychology than in the past. The increasing popularity of computer games among a broad range of age groups leads scientists and experts to seek game domain solutions to cognitive based learning abnormalities, especially for younger age groups and children. One of the major advantages of computer graphics and using game-based techniques over the traditional face-to-face therapies is that individuals, especially children immerse in the game’s virtual environment and consequently feel more open to share their cognitive behavioural characteristics naturally. The aim of this work is to investigate the effects of graphical agents on cognitive behaviours to generate more efficient cognitive models

Developing a system for health and safety enhancement and automation in construction sites

The construction industry forms an important element within the economic activities and is known to be challenging and dangerous. Erroneously construction site accidents were accepted as unavoidable. The existing work health and safety protocols goals were not to cut risk but to provide risk assessment by understanding the types of risks associated with various activities and setting out rules and procedures to manage them and cut their impact. This study attempts a proactive approach to construction site health and safety by anticipating the hazards associated with a planned daily work activity and providing on site the relevant training and safety instructions. This was achieved by integrating the project’s digital design with site images processing and analysis. Digital image processing applies signal processing algorithms to images and videos resulting in extracting useful information from them. An essential and critical issue in the field of computer vision is the object’s recognition methods which should be capable of finding the partial occlusion of objects. Knowledge management systems archive and locate the required information and make it available to the relevant destination quickly and efficiently. It can also provide access to information in other construction sites and to the design team. This management system helps to save the gained experience and make it available to the project or other similar projects. The Building Information System was introduced as a system in which the objectives of this study can be incorporated leaving the door open to incorporate other project management activities. The possible solutions for the identified health and safety business problem were analysed in order to arrive at the best solution suitable to the objectives of the study. The end users ‘needs obtained from the distributed questionnaire and the project’s functional requirements were considered in order to create a model that will achieve their goals in an efficient manner. An activity diagram and a user case diagram based on the UML language were generated. Based on them a computerized model (CONSTRUCTION AUTOMATA) was developed to identify risks associated with specific work activities and provide the relevant safety instructions and training to mitigate them. The model automatically produces safety reports to record and serve as a knowledge management base for future reference thus eliminating possible human errors. The computer program was tested with available site images from an existing project and it proved to deliver its outputs according to its design. The developed model was then demonstrated to a selected group of relevant professionals and was seen to score well with ease of use mark of (6.17) and effectiveness as a health and safety tool mark of (6.37) out of a total mark of (10)

Development of a model-based algorithm for the assessment of the Obsessive-Compulsive Disorder

Questa tesi presentata AAS-PD (Sistema di Assessment Adattivo per i disturbi psicologici), un sistema computerizzato di assessment psicologico adattivo per il Disturbo Ossessivo-Compulsivo (DOC). Tale sistema software è basato su una rappresentazione forma del DOC, chiamata Formal Psychological Assessment (FPA), e rappresenta una novità nel campo della psicologia clinica. AAS-PD prende una struttura di conoscenza (struttura clinica), ed esegue l'assessment facendo inferenze probabilistiche su tale struttura, usando come criterio di stop la misura dell'entropia della struttura. I risultati mostrano che AAS-PD assegna correttamente pattern di risposta a stati clinici, evidenziando inoltre alcuni miglioramenti del modello formale da fare. Sviluppi futuri comportano lo sviluppo di un vero e proprio software capace di supportare il clinico nell'assessment dei principali disturbi psicologici / This thesis presents AAS-PD (Adaptive Assessment System for psychological disorders), a computerized adaptive psychological assessment system for the Obsessive-Compulsive Disorder (OCD). This software system is based on a formal representation of the OCD called Formal Psychological Assessment (FPA), and represents an innovation in the field of clinical psychology. AAS-PD requires a knowledge structure (clinical structure), and performs the assessment by making probabilistic inferences of such a structure, using as stop criterion the measure of entropy of the structure. The results show that PD-AAS properly assigns response patterns to clinical states, and note some improvements of the formal model to do. Future developments will involve the development of a real software that supports the clinician in the assessment of the major psychological disordersope