Appraisal of Optimum Economic Life for Farm Tractor: A Case Study

Agricultural equipment gets deteriorated mechanically and their functionality decreased with time and usage. In order to manage such equipment, it requires higher operating and maintenance cost, as a result of this, there is a need to replace them. Decision making about the replacement of used farm equipment with a new similar one is one of the important aspects of farm machinery management. Based on that criterion, the objective of the investigation was decided to estimate the economic operational life of tractors in the central region of Madhya Pradesh, India and to evaluate the effect of different parameters on economic life, which would add value to the profitable management decision. The tractor data collected were from government agricultural centres in the different regions of M.P. and categorized them into different groups based on their horsepower rating. Considering the preventive replacement policy the total annual average costs of tractors were estimated taking account into the repair cost and depreciation cost. The time period (in year), when the total annual average cost touched its minimum value, was decided as the economic life of a tractor. There is a negative correlation (r= -0.835) found between size (HP) of tractors and their economic life. And an empirical relation based on multiple regression analysis has been generated to predict the economic operational life of a tractor using per unit repair cost and annual usage (hours) as variables

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

The effect of increasing the thickness of the ship’s structural members on the Generalised Life Cycle Maintenance Cost (GLCMC)

In the context of the EU funded IMPROVE project, the research work of a Generalised Life Cycle Maintenance Cost (GLCMC) was initiated in order to investigate the influence of a weight oriented ship structural design on its production and operational characteristics. Following this, an increase in the structural scantlings of the ship was examined following the IACS Common Structural Rules (CSR) for double hull oil tankers. A case study for a Chemical tanker is shown considering an addition in its bottom plate thickness and three different cases of mean annual corrosion rates applied. A comparison regarding the “Gross gains”, “Gross expenses” and “Net gains” for this ship is also presented. Moreover, an evaluation of the extra cost for the additional steel weight used is shown together with the outcome on the repair-free operation of the ship for different additional plate thickness. Finally, a sensitivity analysis is carried out for the most likely case (“Case 2”) and the variation of different amount of days spent in the ship repair yard

Studies of tractor maintenance and replacement strategies of Wonji Shoa Sugar Factory, Ethiopia

This study mainly focuses on tractor maintenance and replacement strategies to assess the impact of various parameters on the economic life of tractors in order to improve the value of a profitable management choice on selected tractor samples. Considering the preventive replacement policy, the total annual costs were estimated taking account into the repair cost and depreciation costs. At a 95 % level of confidence for each approach, the statistical analysis program "IBM SPSS Statistics 26" was used. An empirical relation based on multiple regression analysis has been generated to predict the economic operational life of a tractor using per-unit repair cost and annual usage (hours). From the analysis, John Deere (9330R), SAME (SAME130), New Holland (NH 80), and Massey Ferguson (MF150) are not supposed to be economical to use in the field after the fifth, seventh, sixth, and eighth years respectively at Wonji Shoa sugar factory due to increasing maintenance cost in present condition

Introduction in IND and recursive partitioning

This manual describes the IND package for learning tree classifiers from data. The package is an integrated C and C shell re-implementation of tree learning routines such as CART, C4, and various MDL and Bayesian variations. The package includes routines for experiment control, interactive operation, and analysis of tree building. The manual introduces the system and its many options, gives a basic review of tree learning, contains a guide to the literature and a glossary, and lists the manual pages for the routines and instructions on installation

Operations Management

Global competition has caused fundamental changes in the competitive environment of the manufacturing and service industries. Firms should develop strategic objectives that, upon achievement, result in a competitive advantage in the market place. The forces of globalization on one hand and rapidly growing marketing opportunities overseas, especially in emerging economies on the other, have led to the expansion of operations on a global scale. The book aims to cover the main topics characterizing operations management including both strategic issues and practical applications. A global environmental business including both manufacturing and services is analyzed. The book contains original research and application chapters from different perspectives. It is enriched through the analyses of case studies

DECISION-MAKING FRAMEWORK FOR THE SELECTION OF SUSTAINABLE ALTERNATIVES FOR ENERGY-RETROFITS

Buildings are major consumers of energy worldwide. On the other hand, over 60% of the US housing inventory is over 30 years old and a large number of these homes are energy inefficient. Therefore, it is essential to target the existing building stock for energy efficient interventions as a key to substantially reduce the adverse impacts of buildings on the environment and economy. Building energy retrofitting has emerged as a primary strategy for reducing energy use and carbon emissions in existing buildings. An energy retrofit can be defined as a physical or operational change in a building, its energy-consuming equipment, or its occupants\u27 energy-use behavior to convert the building to a lower energy consuming facility. Energy retrofitting could result in additional sustainable benefits such as reducing maintenance costs, reducing air emissions, creating job opportunities, enhancing human health, and improving thermal comfort among others. One of the main challenges in building energy retrofitting is that several combinations of applicable energy consumption reducing measures can be considered to retrofit a building and it is a difficult task to choose the best retrofit strategy. Although numerous resources provide advice on how to retrofit a building, decisions regarding the optimal combination of retrofitting measures for a specific building are typically complex. In addition, most of the decisions for energy retrofits are based on limited cost categories rather than environmental and social considerations. The main goal of this study is to develop a decision support system that integrates sustainable criteria (i.e. economic, environmental, and social benefits) in decision-making in energy retrofits. This goal will achieved through following objectives: (1) Determining the impact of building life-cycle on energy retrofitting decision-making; (2) Identifying and quantifying the sustainable benefits of building energy retrofitting to be used as an objective function in optimization problems; (3) Developing a systematic approach to select among different sustainable decision criteria for energy retrofitting decision-making; and (4) Developing and demonstrating a decision-making optimization model to select the best energy retrofitting alternative for a specific building while maximizing its sustainable benefits. First a life-cycle cost analysis of the case study is presented in terms of energy retrofitting. This life-cycle cost analysis is used to explore the process of decision-making in energy retrofits. Then, a comprehensive study on identifying and quantifying the sustainable benefits of energy retrofits is performed that can be used in decision-making. Different tools such as literature review, surveys, Delphi technique, concept mapping approach, hedonic price modeling, and statistical analysis are used in this step. After that, a Sustainable Energy Retrofit (SER) decision support system is proposed. Finally, the application of this decision support system on a case study of a house located in Albuquerque, New Mexico is explored. This research contributes to the body of knowledge by: (1) Integrating sustainable impacts of building energy retrofits (i.e. Economic, Environmental, and social) in decision-making; (2) Proposing a decision matrix that guides decision-makers on how to select the objective function(s) to formulate an optimization problem that results in the selection of the best energy retrofitting strategy, considering the benefits to investors; (3) Introducing a novel simplified energy prediction method by integrating dynamic and static modeling; (4) Measuring the implicit price of energy performance improvements in the US residential housing market; (5) Identifying, categorizing, and mapping the social sustainability criteria of energy improvements in existing buildings; and last but not least (6) Developing a decision-support system for energy retrofitting projects that integrates the above approaches. The energy retrofitting decision-making model developed in this research can be implemented for different types of buildings to help decision-makers select the optimum energy retrofit strategy that not only maximizes monetary benefits, but also maximize environmental and social benefits. The presented research can also help homeowners to plan or evaluate their retrofitting strategies

Development and Application of an Optimum Machinery Complement Selection System

Agricultural Economic

Working Notes from the 1992 AAAI Spring Symposium on Practical Approaches to Scheduling and Planning

The symposium presented issues involved in the development of scheduling systems that can deal with resource and time limitations. To qualify, a system must be implemented and tested to some degree on non-trivial problems (ideally, on real-world problems). However, a system need not be fully deployed to qualify. Systems that schedule actions in terms of metric time constraints typically represent and reason about an external numeric clock or calendar and can be contrasted with those systems that represent time purely symbolically. The following topics are discussed: integrating planning and scheduling; integrating symbolic goals and numerical utilities; managing uncertainty; incremental rescheduling; managing limited computation time; anytime scheduling and planning algorithms, systems; dependency analysis and schedule reuse; management of schedule and plan execution; and incorporation of discrete event techniques