“…The types of efficiency generated by the DEA were calculated: (1) standard efficiency; (2) inverted frontier; and 3composite efficiency. For this analysis, composite efficiency was used, which consisted of a mean between the DMUs with best and worst performances (Piran et al 2016(Piran et al , 2017Barbosa et al 2017;Souza et al 2018;Telles et al 2020). The inverted frontier of technical efficiency or IDEA evaluates the inefficiency of a DMU, constructing a frontier constituted of units with the worst managerial practices.…”
Section: Methodsmentioning
confidence: 99%
“…DEA is an approach used to measure the efficiency of decision-making units (DMUs), which have multiple inputs and outputs (Barbosa et al 2017;Souza et al 2018). Through the DEA, it is possible to identify a set of DMUs that form an efficient frontier (Bulak and Turkyilmaz 2014;Kundi and Sharma 2015).…”
Section: Data Envelopment Analysis (Dea)mentioning
The efficiency levels at which companies turn inputs into outputs may increase their competitive capacity. Nevertheless, in the literature, there is a lack of methods allowing evaluation of the performance of operations in production systems that take into account all of their components. The objective of this study is to present an analysis of efficiency for a production system using DEA and OEE in an integrated manner (DEA/OEE). To achieve this objective, we conducted a case study of a bus manufacturer and a comparative analysis using the results obtained by DEA/OEE compared with the results of the OEE measured in an operation of the company studied. The efficiency measured by DEA/OEE presents differences in relation to OEE results. The analysis of the causes of such differences pointed out that action taken to improve the OEE indicator decreased the efficiency of the operation analyzed. This study evidences that decision-making focused on improving OEE on its own may lead to an increase in the consumption of resources during an operation. Such an increase does not necessarily increase production levels and may reduce technical efficiency.
“…The types of efficiency generated by the DEA were calculated: (1) standard efficiency; (2) inverted frontier; and 3composite efficiency. For this analysis, composite efficiency was used, which consisted of a mean between the DMUs with best and worst performances (Piran et al 2016(Piran et al , 2017Barbosa et al 2017;Souza et al 2018;Telles et al 2020). The inverted frontier of technical efficiency or IDEA evaluates the inefficiency of a DMU, constructing a frontier constituted of units with the worst managerial practices.…”
Section: Methodsmentioning
confidence: 99%
“…DEA is an approach used to measure the efficiency of decision-making units (DMUs), which have multiple inputs and outputs (Barbosa et al 2017;Souza et al 2018). Through the DEA, it is possible to identify a set of DMUs that form an efficient frontier (Bulak and Turkyilmaz 2014;Kundi and Sharma 2015).…”
Section: Data Envelopment Analysis (Dea)mentioning
The efficiency levels at which companies turn inputs into outputs may increase their competitive capacity. Nevertheless, in the literature, there is a lack of methods allowing evaluation of the performance of operations in production systems that take into account all of their components. The objective of this study is to present an analysis of efficiency for a production system using DEA and OEE in an integrated manner (DEA/OEE). To achieve this objective, we conducted a case study of a bus manufacturer and a comparative analysis using the results obtained by DEA/OEE compared with the results of the OEE measured in an operation of the company studied. The efficiency measured by DEA/OEE presents differences in relation to OEE results. The analysis of the causes of such differences pointed out that action taken to improve the OEE indicator decreased the efficiency of the operation analyzed. This study evidences that decision-making focused on improving OEE on its own may lead to an increase in the consumption of resources during an operation. Such an increase does not necessarily increase production levels and may reduce technical efficiency.
“…7, this assessment confirms BARBOSA ET AL. statement that modular systems achieve significant product differentiation and variation while simultaneously reducing costs through economies of scale [1]. Fig.…”
Section: Experimental Design Materials and Methodsmentioning
Today, many companies develop modular systems to realise considerable product differentiation and variation while simultaneously reducing costs through economies of scale [1]. Designing these modular systems to be lasting and robust in a highly dynamic environment [2], avoiding subsequent modification cost [3,4] and staying innovative over the product lifecycle is crucial for sustainable success in an increasingly competitive market [5]. Two closely related surveys were carried out on the initial situation described above. The first survey deals with the major conflict between planning reliability and flexibility with regard to future boundary conditions that the described challenges lead to. The data presented in this article on the first survey was collected from German companies, mainly from the automotive industry, developing and manufacturing complex products using modular systems. Other represented companies operate in the machine and plant construction industry. The survey comprises the answers of 39 participants, gathered via online questionnaire. The 17 questions of the survey are divided into two topics: characteristics of the participants, and the problem description of modular systems in highly dynamic environments and the management thereof. The second survey deals with the anticipation of innovations in the design of modular systems and the selection of the right choice from a variety of possible innovations to be considered. The data presented in this article on the second survey was collected from German automotive manufacturers, which develop and manufacture complex products using modular systems. The survey comprises the answers of 501 participants, gathered via online questionnaire. The 14 questions of the survey are divided into two topics: characteristics of the participants, and the problem description of modular systems and the management thereof. The data obtained allows the identification of existing deficits and dedicated research on solutions.
“…Modularization is considered as an important way to improve the product quality in both academic and practice areas [28], [1], [29] and thus, it helps the firm gaining competitive advantage in the market [24], [3]. To enhance the capability, modularity design is integrated with many production theories and applications, such as Engineer-To-Order (ETO) industries at the beginning of product design [17], the customer quality [29], the performance of manufacturing and product [7], the developing cycle of new product [26], production flexibility coping with supply interruption [9], and a return policy in a two echelon supply chain [5].…”
Section: Feng Tao Hao Shao and Kinkeung Laimentioning
This paper considers price and modularity of competition between two firms with deterministic demand, in which demand is dependent on both the prices and the modularity levels determined by two firms. Bertrand competition and Stackelberg competition are formulated to derive the equilibrium solutions analytically. Because of the complexity, an intensive numerical study is conducted to investigate the impact of the sensitive parameters on equilibrium prices and modularity levels, as well as optimal profits of the two firms. An important and interesting finding is that optimal profits of the two firms under both types of competition are decreasing with the modularity cost when the price and modularity sensitivities are low, where both firms are worse-off due to decrease of the modularity levels; but they are increasing when the price and modularity sensitivities are high, where both firms are better-off at the expense of modular design. Our research reveals that Stackelberg game improves the modularity levels in most of the cases, though both firms perform better in Bertrand competition in these cases when jointly deciding the prices and modularity levels in the two firms.
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