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Decision-Making Grid (DMG) is used for determining maintenance tactics and is associated with the reliability and risk management of assets. In this grid, decision making is performed based on two indicators of Mean Time to Repair (MTTR) and frequency of failures. The purpose of this paper is to improve DMG by recognizing interdependence among failures.

Fault Tree Analysis and Reliability Block Diagram have been applied for improving DMG. The proposed approach has been examined on eight equipment of the steel making and continuous casting plant of Mobarakeh Steel Company.

Findings indicate different positions of equipment in the cells of the new grid compared to the basic grid.

DMG is limited to two criteria of frequency of failures and MTTR values. In both basic and new DMGs, cost analysis has not been performed. The application of the proposed approach will help the reliability/maintenance engineers/analysts/managers to allocate more suitable maintenance tactics to equipment. This, in turn, will enhance the equipment life cycle and availability as the main objectives of physical asset management.

A major limitation of basic DMG is that the determined tactic based on these two indicators might not be an appropriate solution in all conditions, particularly when failures are interdependent. This has been resolved in this paper.

The paper analyzes the relative performance of provincial gas distribution companies with different types of inputs and outputs. A data envelopment analysis (DEA)-based model is developed to construct an equilibrium efficient frontier in the presence of multi-type input/output variables.

A DEA-based model is developed to construct an equilibrium efficient frontier in the presence of multi-type input/output variables.

It has been shown that using this single equilibrium efficient frontier, a trade-off is made between efficient and inefficient companies so as to make all companies as efficient.

The study analyzes the relative performance of provincial gas distribution companies with different types of inputs and outputs. A DEA-based model is developed to construct an equilibrium efficient frontier in the presence of multi-type input/output variables. It has been shown that using this single equilibrium efficient frontier, a trade-off is made between efficient and inefficient companies so as to make all companies as efficient.

The purpose of this paper is to find the proper statistical distribution function, which can cover the failure time of a single machine or a group of machines. To this end, an innovative program is written in an Excel software, capable of assessing at least six statistical distribution functions. This research study intends to show the advantages of applying statistical distribution functions in an integrated model format to create or increase productive reliability machines. Productive reliability is a simultaneous combination of efficiency and effectiveness in reliability.

The method of theoretical research methodology comprises data collection tools, reference books and articles in addition to exploiting written reports of the Iranian Center for Defence’s Standards. The practical research method includes deploying and assessing the proposed model for a selected machine (in this case a computerized numerical control machine).

A comprehensive program in an Excel software having the capability of assessing at least six statistical distribution functions was developed to find the most efficient option for covering the failure times of each machine in the shortest time with the highest precision. This is regarded as the most important achievement of the present study. Furthermore, the advantages of applying the developed model are discussed and a large group of which have direct influences on the productivity of equipment reliability.

The originality of the research was ascertained by managers and experts working in maintenance issues at the different levels of the Defense Industries Organization.

This paper addresses special reliability-centered maintenance (RCM) strategies for one-shot devices by providing fuzzy inferences system with the assumption that, to data, there is no data available on their maintenance. As far as one-shot devices are concerned, the relevant data is inadequate.

In this paper, a fuzzy expert system is proposed to effectively select RCM strategies for one-shot devices. In this research: (1) a human expert team is provided, (2) spatial RCM strategies for one-shot devices and parameters bearing upon those strategies are determined, (3) the verbal variables of the expert team are transformed into fuzzy sets, (4) the relationship between parameters and strategies are designed whereupon a model is developed by MATLAB software, (5) Finally, the model is applied to a real-life one-shot system.

The finding of this study indicates that the proposed fuzzy expert system can determine the parameters affecting the choice of the appropriate one-shot RCM strategies, and a fuzzy inference system can help for effective decision making.

The developed model can be used as a fast and reliable method for determining an appropriate one-shot RCM strategy, whose results can be relied upon with a suitable approximation in respect of the behavior test. To the best authors’ knowledge, this problem is not addressed yet.

This chapter of the book seeks to use famous mathematical functions (statistical distribution functions) in evaluating and analyzing supply chain network data related to supply chain management (SCM) elements in organizations. In other words, the main purpose of this chapter is to find the best-fitted statistical distribution functions for SCM data. Explaining how to best fit the statistical distribution function along with the explanation of all possible aspects of a function for selected components of SCM from this chapter will make a significant attraction for production and services experts who will lead their organization to the path of competitive excellence. The main core of the chapter is the reliability values related to the reliability function calculated by the relevant chart and extracting other information based on other aspects of statistical distribution functions such as probability density, cumulative distribution, and failure function. This chapter of the book will turn readers into professional users of statistical distribution functions in mathematics for analyzing supply chain element data.

This chapter of the book aims to introduce multiobjective linear programming (MLP) as an optimum tool to find the best quality engineering techniques (QET) in the main domains of supply chain management (SCM). The importance of finding the best quality techniques in SCM elements in the shortest possible time and at the least cost allows all organizations to increase the power of experts’ analysis in supply chain network (SCN) data under cost-effective conditions. In other words, this chapter aims to introduce an operations research model by presenting MLP for obtaining the best QET in the main domains of SCM. MLP is one of the most determinative tools in this chapter that can provide a competitive advantage. Under goal and system constraints, the most challenging task for decision-makers (DMs) is to decide which components to fund and at what levels. The definition of a comprehensive target value among the required goals and determining system constraints is the strength of this chapter. Therefore, this chapter can guide the readers to extract the best statistical and non-statistical techniques with the application of an operations research model through MLP in supply chain elements and shows a new innovation of the effective application of operations research approach in this field. The analytic hierarchy process (AHP) is a supplemental tool in this chapter to facilitate the relevant decision-making process.

Human developments in constructing buildings and their subsequent infrastructures despite certain advantages have unfortunately considerable effects on the environment, such that construction could be named as the main exploiter of the natural, physical and biologic resources. Hence, the purpose of this paper is to evaluate the effect of communication capabilities of the suppliers and external green integration on the green performance and financial performance of engineering and construction companies.

The statistical population of the study comprises all 300 members of the Building Engineering System of South Khorasan Province. According to the Morgan table (1972), 167 participants were selected as the sample of the study using the stratified random sampling, and a standard questionnaire was distributed among them. Data were collected through library and filed methods. Data were analyzed using the factor analysis method (SPSS), and LISREL Software was used for evaluating the research hypotheses.

The obtained results indicated that information sharing has a significant effect on environmental coordination and the green balance of green cost reduction of coordinate competitive advantage.

Accordingly, given the results obtained from a developmental-practical research, the authors initially gathered and classified the required data on the construction industry using the library and field methods, then extracted the obstacles of the supply chain to help facilitate the implementation of efficiency in the so-called industry.