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The purpose of this paper is to develop a double-objective economic statistical design (ESD) of (X ‾) control chart under Weibull failure properties with the Linex asymmetric loss function. The authors have expressed the probability of type II error (β) as the statistical objective and the expected cost as the economic objective.

The design used in this study is based on a double-objective economic statistical design of (X ‾) control chart with Weibull shock model via applying Banerjee and Rahim's model for non-uniform and uniform schemes with Linex asymmetric loss function. The results in the least average cost and β in uniform and non-uniform schemes by Linex loss function, compared with the same schemes without loss function.

Numerical results indicate that it is not possible to reduce the second type of error and costs at the same time, which means that by reducing the second type of error, the cost increases, and by reducing the cost, the second type of error increases, both of which are very important. Obtained based on the needs of the industry and which one has more priority has the right to choose. These designs define a Pareto optimal front of solutions that increase the flexibility and adaptability of the X ‾ control chart in practice. When the authors use non-uniform schemes instead of uniform schemes, the average cost per unit time decreases by an average and when the authors apply loss function, the average cost per unit time increases by an average. Also, this quantity for double-objective schemes with loss function compared to without loss function schemes in cases uniform and non-uniform increases. The reason for this result is that the model underestimated the costs before using the loss function.

This research adds to the body of knowledge related to flexibility in process quality control. This article may be of interest to quality systems experts in factories where the choice between cost reduction and statistical factor reduction can affect the production process.

The cost functions for double-objective uniform and non-uniform sampling schemes with the Weibull shock model based on the Linex loss function are presented for the first time.

The objective of the paper is to present a model for the environmental value analysis (EVA) and its usefulness as tool towards environmental improvement analysis. A new concept called EVA, which focuses on integrating environmental issues with value analysis, is proposed in this paper. The mathematical model of environmental value index (EVI), which is derived from EVA analysis, aims to define the relationship between the importance of the environmental functions and the cost of the functions. The development of EVI provides the basis for generating feasible alternatives, which are performed simultaneously. By determining the EVIs, this approach ensures prioritisation, and thereby predicts a better set of environmental improvement alternatives. Three case studies are used to illustrate the implementation of EVA methodology.

This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

This chapter examines the main methodological issues involved in the comprehension of the cost structure of the airport industry and suggests considerations for future airport cost analyses. Such understanding has become a crucial concern for policy makers, regional planners, and managers in order to deal with optimal market design (e.g., regulation and market configuration) and airport strategies (e.g., pricing, investments, and alliances). An in-depth analysis of the economics of cost functions is presented, together with a description of the relevant multi-output cost economies measures (average incremental costs, scale and scope economies, and cost complementarities). We also discuss the assumptions underlying estimates of total versus variable cost functions and the importance of estimating a sufficiently flexible functional form. Moreover, we provide a critical survey of the international empirical literature on the cost structure of the airport industry, which highlights how econometric estimates strongly depend on the sample choice and the empirical model considered. Indeed, while econometric studies on international samples based on long-run cost function estimates show that long-run scale economies are never exhausted, single country studies mostly estimate variable cost functions and find lower values for scale economies at median sample points that tend to decrease with size. We discuss why we believe that studies based on the estimation of short-run variable cost functions offer more reliable results, given the reasonable assumption of airport overcapitalization in the short run. We conclude our work by noting that underlying policy issues related to planning and regulation, as well as to the optimal market structure of the airport sector, need to take into account the role played by vertical relationships between airports and airlines.

Production‐cost duality was first introduced by Ronald Shephard (1953) in his seminal study, Cost and Production Functions. The application of duality to production and cost was extended by Uzawa (1962, 1964). However, not until the 1970s did the Shephard‐Uzawa duality analysis achieve its influential role in modern microeconomic thought. In simple words, the Shephard‐Uzawa duality theorem indicates that a firm's cost function summarizes all of the relevant features of the production technology, whereas the firm's production function contains all of the relevant features of the cost function for each set of input and output prices. If certain standard technical conditions (i.e., relating to convexity and continuity) are satisfied, then the theorem implies that there is a one‐to‐one relationship between points on the cost surface and points on the production surfaces.

This paper presents an approach for short‐term maintenance planning, based on information about the technical health of an item. A simple cost/risk model is used to calculate the expected costs when postponing preventive maintenance for an item that is soon to fail, based on the cost of corrective and preventive maintenance and the probability of failure. The probability of failure is calculated on the basis of an underlying probability density function f(t), which is determined from available quantitative and qualitative information. The preventive maintenance cost is time dependent, and can be described either as a general cost function or as a specific cost function. The specific cost function can be derived from stochastic shifts in the maintenance cost for the actual problem at hand.