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This paper focuses on the determination of the cost completion rate used to calculate the equivalent units of production in a continuous process costing system. The paper aims at two research questions. What procedures do companies utilize in practical terms? How should the completion level percentage be calculated conceptually?

The study is a qualitative exploratory survey. The companies targeted were those noted in “Melhores e Maiores,” a ranking of the best and biggest Brazilian companies. A total of 175 questionnaires were sent to pre‐selected enterprises, each with revenues of more than US$100 million per year, and 50 usable responses were returned.

A literature review of the theoretical procedures used for continuous process costing revealed no indication of an objective method for determining the completion level. The empirical research in the present study confirmed that, in practice, companies do not adopt the general procedures proposed by the theory. The best practices applied by the companies have been shown to be an adequate alternative, because the results are identical to those obtained with the proposed method.

The study bears the usual limitations of a qualitative exploratory survey regarding its generalization to other companies.

The originality of the study is based on the assumption that cost accounting theory does not offer an objective solution for the computation of the completion level percentage and, consequently, that companies in continuous process production system do not adopt the theoretical concepts with respect to inventory evaluation of goods‐in‐process and finished goods.

The performance of earthmoving operations, in terms of emissions, production and cost, is dependent on many variables and has been the study of a number of publications. Such publications look at typical operation design and management, without establishing what the penalties or bonuses might be for non-standard, but still observed, practices. To fill this gap in knowledge, this paper examines alternative loading policies of zero waiting-time loading, fractional loading and double-sided loading, and compares the performance of these with standard single-sided loading.

Original recursive relationships, that are amenable to Monte Carlo simulation, are derived. Case study data are used to illustrate the emissions, production and cost penalties or bonuses.

Double-sided loading contributes the least impact to the environment and is the most cost effective. Zero waiting-time loading performs the worst in terms of environmental impact and cost. Minimizing truck waiting times through using fractional loading is generally not an attractive policy because it leads to an increase in unit emissions and unit costs. The consequences of adopting fractional loading are detailed. Optimum unit emissions and optimum unit cost are coincident with respect to fleet size for single- and double-sided loading policies. That is, by minimizing unit cost, as in traditional practice, then least impact on the environment is obtained. Not minimizing unit cost will lead to unnecessary emissions.

The results of this paper will be of interest to those designing and managing earthmoving operations.

All modeling and results presented in the paper do not exist elsewhere in the literature.

Good management strives to align and corporate processes for more attention being paid to supply chain management. Firms realize that greater co-operation and improved coordination can help to manage the entire supply chain more efficiently. The imperfect quality item is one of the most important issues that affect the expected profit of green supply chain. The imprecise cost with screening process of poor quality items posed in supply chain is the subject of this study.

The present study explores production model for imperfect items having uncertain cost parameters with three-layer supply chain encompassing supplier, manufacturer and retailer. The model is considering the impact of business tactics such as order size, production rate, production cost and appropriate times in various sectors on collaborative marketing systems. Due to imprecise cost parameters, the pentagonal fuzzy numbers are set to fuzzify the total cost and defuzzifition by using graded mean integration.

This study offers an explicit condition in uncertain environment to manage the imperfect quality item to increase the potential profit of the supply chain. The influence of changes in parameter values on the optimal inventory policy under fuzziness is provided managerial insights.

This model makes a significant contribution to fuzzy inference. The results of the study provide a trading strategy for the industry to avoid losses. The prescribed study can be suitable for the industries like sculpture, jewelry, pottery, etc.

The purpose of this paper is to consider various possible constraints of the problem of production and maintenance planning control for a multi-machine under subcontracting constraint, in order to bring the manufacturer industry closer to real mode. In this paper, we present an efficient and feasible optimal solution, by comparing optimization procedures.

Our manufacturing system is composed of parallel machines producing a single product, to satisfy a random demand under a given service level. In fact, the demand is greater than the total capacity of the set of machines; hence there rises a necessity of subcontracting to complete the missing demand. In addition, we consider that the unit cost of subcontracting is a variable depending on the quantity subcontracted. As a result, we have developed a stochastic optimal control model. Then, to solve the problem we compared three optimization methods: (exact/approximate), the genetic algorithm (GA), the Pattern Search (PS) and finally fmincon. Thus, we validate our approach via a numerical example and a sensitivity analysis.

This paper defines an internal production plan, a subcontracting plan and an optimal maintenance strategy. The optimal solution presented in this paper significantly improves the ability of the decision maker to consider larger instances of the integrated model. In addition, the decision maker can answer the following question: Which is the most optimal subcontractor to choose?

The approach developed deals with the case of the real-mode manufacturing industry, taking into consideration different constraints and determining decision variables which allow it to expand the profits of the manufacturing industry in different domains such as automotive, aeronautics, textile and pharmacies.

This paper is one of the few documents dealing with the integrated maintenance in subcontracting constraint production which considers the complex aspect of the multi-machine manufacturing industry. We also dealt with the stochastic aspect of demand and failures. Then, we covered the impact of the unit cost variation of subcontracting on the total cost. Finally, we shed light on a comparison between three optimization methods in order to arrive at the most optimal solution.

To achieve a full understanding of the role of marketing from plan to profit requires a knowledge of the basic building blocks. This textbook introduces the key concepts in the art or science of marketing to practising managers. Understanding your customers and consumers, the 4 Ps (Product, Place, Price and Promotion) provides the basic tools for effective marketing. Deploying your resources and informing your managerial decision making is dealt with in Unit VII introducing marketing intelligence, competition, budgeting and organisational issues. The logical conclusion of this effort is achieving sales and the particular techniques involved are explored in the final section.

Aim of the present monograph is the economic analysis of the role of MNEs regarding globalisation and digital economy and in parallel there is a reference and examination of some legal aspects concerning MNEs, cyberspace and e‐commerce as the means of expression of the digital economy. The whole effort of the author is focused on the examination of various aspects of MNEs and their impact upon globalisation and vice versa and how and if we are moving towards a global digital economy.

This paper examines how target costing decisions can be impacted by product and production interdependencies.

Numerical examples are used to investigate the effect that product and production interdependencies have on target costing decisions. Mixed integer programming and simulation are used to model the interrelationships between a product’s cost reduction effort and related decisions such as product mix, pricing, and capacity acquisition. Product and production interdependencies are introduced by evaluating a product with multiple price and demand options, capacity is acquired in large discrete quantities, and resources have economies of scale. Analyses of choices made with and without considering product and production interdependencies are used to evaluate their effects on target costing decisions.

A product’s cost reduction effort cannot be determined independently of other production-related choices, such as product mix, capacity, and price, in the presence of product and production interdependencies.

The findings of this paper underscore the need for additional research to understand the conditions that impair target costing decisions and the economic consequences of suboptimal decisions.

Rather than assessing target costing decisions at the individual product level, these decisions must be evaluated at the portfolio level of the firm’s operations.

Suboptimal target costing decisions impact the products and product mix that the firm chooses to offer, which affects the ability of organizations to effectively achieve their strategic goals.

This paper identifies new limitations to target costing that can help managers understand the technique better and lead to improved target costing decisions.

The main contribution of this manuscript is to suggest new approaches in order to deal with dynamic lot-sizing and maintenance problem under aspect energetic and risk analysis. The authors introduce a new maintenance strategy based on the centroid approach to determine a common preventive maintenance plan for all machines to minimize the total maintenance cost. Thereafter, the authors suggest a risk analysis study further to unforeseen disruption of availability machines with the aim of helping the production stakeholders to achieve the obtained forecasting lot-size plan.

The authors tackle the dynamic lot-sizing problem using an efficient hybrid approach based on random exploration and branch and bound method to generate possible solutions. Indeed, the feasible solutions of random exploration method are used as input for branch and bound to determine the near-optimal solution of lot-size plan. In addition, our contribution to the maintenance part is to determine the optimal common maintenance plan for M machines based on a new algorithm called preventive maintenance (PM) periods means.

First, the authors have funded the optimal lot-size plan that should satisfy the random demand under service level requirement and energy constraint while minimizing the costs of production and inventory. Indeed, establishing a best lot-size plan is to determine the appropriate number of available machines and manufactured units per period. Second, for risk analysis study, the solution of subcontracting is proposed by specifying a maximum cost of subcontractor in the context of a calling of tenders.

For maintenance problem, the originality consists in regrouping the maintenance plans of M machines into only one plan. This approach lets us to minimize the total maintenance cost and reduces the frequent breaks of production. As a second part, this paper contributed to the development of a new risk analysis study further to unforeseen disruption of availability machines. This risk analysis developed a decision-making system, for production stakeholders, in order to achieve the forecasting lot-size plan and keeps its profitability, by specifying the unit cost threshold of subcontractor in the context of a calling of tender.

The purpose of this paper is to propose an economic production quantity (EPQ) inventory model considering imperfect items and probabilistic demand for a two-echelon supply chain. The production process is imperfect and the imperfect quality items are removed from the lot size. The demand rate of the inventory system is random and follows an exponential probability density function and the demand of the retailers is depending on the initiatives of the sales team.

Two approaches are examined. In the non-collaborative approach, any member of the supply chain can be the leader and takes decisions to optimize the profits, and in the collaborative system, all members make joint decisions about the production, supply, sales and inventory to optimize the profits of the supply chain members. The calculus approach is applied to find the maximum profit related to the members of the supply chain.

A numerical example is presented to illustrate the performance of the EPQ model. The results show that collaborative approach generates greater profits to the supply chain and the market’s demand represents the variable behavior and uncertainty that is generated in the replenishment of a supply chain.

The new and major contributions of this research are: the inventory model considers demand for products is random variable which follows an exponential probability distribution function and it also depends on the initiatives of sales teams, the imperfect production system generates defective items, different cycle time are considered in manufacturer and retailers and collaborative and non-collaborative approaches are also studied.

This paper aims at analyzing different possible assembly systems, including innovative potential configurations such as the fully flexible assembly systems (FAS), by defining a novel analytical model that focuses on the concept of agility and its impact on the whole system performance, also evaluating the economic convenience in terms of the unit direct production cost.

The authors propose a comparison model derived by Newton’s second law, introducing a quantitative definition of agility (acceleration), resistance of an assembly system to any change of its operative state (inertia) and unit direct production cost (force). Different types of assembly systems (manual, flexible and fully FAS) are analyzed and compared using the proposed model, investigating agility, system inertia and their impact on the unit direct production cost.

The proposed agility definition and the proposed comparison model have been applied considering different sets of parameters as independent variables, such as the number of components to assemble (product model complexity) and the target throughput of the system. The main findings are a series of convenience areas which either, for a given target unit direct production cost (force), defines the most agile system to adopt or, for a given target agility (acceleration), defines the most economical system to adopt, as function of the independent variables.

The novelty of this work is, first, the analytical definition of agility applied to assembly systems and contextualized by means of the definition of the new comparison model. The comparison between different assembly systems on the basis of agility, and by using different sets of independent variables, is a further element of interest. Finally, the resulting convenience areas represent a desirable tool that could be used to optimally choose the most suitable assembly system according to one or more system parameters.