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The purpose of this paper is to analyze the impacts of Portfolio size effect due to scaling issues in the outcome obtained in a project portfolio selection for an electricity company in Brazil, focusing on improving business strategic performance.

The study uses a web-based decision support system (DSS), in which scaling issues are considered, incorporating results of previous work. The study evaluates 32 projects from the electricity company and compared the possible results when considering different scales. Additionally, a sensitivity analysis was conducted to analyze the robustness of the case, using the web-based DSS.

The results for an interval scale context showed a portfolio with 21 projects, contrasting with the correct solution of a portfolio containing 23 projects. The latter is related to a ratio scale context, with the proper transformation of weights, which was found to be robust with a sensitivity analysis using Monte Carlo simulation. This demonstrates that only appropriate models for selecting projects can improve the contribution to the company’s permanent strategies of increasing productivity, considering its constraints to achieve optimal results.

Additive value functions approach imposes certain requirements on the measurement scales used for the items in a portfolio that should not be ignored, once they have significant impact on the general portfolio results, which are directly related to the business strategic performance and the facilities of doing that with a web-based DSS.

The purpose of this paper is to review maintenance strategies within the healthcare domain and to discuss practical needs as gaps between research and practice.

The paper systematically categorizes the published literature on clinical maintenance optimization and then synthesizes it methodically.

This study highlights the significant issues relevant to the application of dependability analysis in healthcare maintenance, including the quantitative and qualitative criteria taken into account, data collection techniques and applied approaches to find the solution. Within each category, the gaps and further research needs have been discussed with respect to both an academic and industrial perspective.

It is worth mentioning that medical devices are becoming more and more numerous, various and complex. Although, they are often affected by environmental disturbances, sharp technological development, stochastic and uncertain nature of operations and degradation and the integrity and interoperability of the supportability system, the associated practices related to asset management and maintenance in healthcare are still lacking. Therefore, the literature review of applied based research on maintenance subject is necessary to reveal the holistic issues and interrelationships of what has been published as categorized specific topics.

The paper presents a comprehensive review that will be useful to understand the maintenance problem and solution space within the healthcare context.

The purpose of this paper is to develop a model that permits more rational planning for preventive maintenance, by controlling failures in the specific context of equipment breakdown. Thus not only the cost and reliability parameters are dealt with, but also the peculiarities of different contexts in which maintenance activities occur. Furthermore, it aims to include Bayesian methodology in the procedure to overcome main difficulties in failure data.

A multi‐criteria decision‐aiding model capable of overcoming the two main difficulties related to preventive maintenance: establishing a replacement periodicity based on more than one criterion, and the ability to provide a solution in uncertainties situations, has been developed from adaptation of classical models. This model also uses Bayesian elements to address uncertainties during equipment failures.

The paper finds that in a preventive maintenance planning, as a multi‐criteria decision problem, different types of uncertainties may be identified, which may be categorized as external uncertainties and internal uncertainties. In the proposed model a division of procedures has been established, dealing with external uncertainties first, then the internal uncertainties related to the structure of the problem and analysis of the decision are addressed using the multi‐criteria decision‐making method PROMETHEE III that allows the amplification of the notion of indifference. In this way, a suitable structure to connect two types of uncertainties was structured.

The model will assist the decision‐maker in preventive maintenance planning to take uncertainties into account, seeing the alternatives that are closest, through an amplification of the notion of indifference provided by PROMETHEE III. Furthermore, in practice the proposed model have an impact on maintenance cost and reliability of production plant.

This paper proposes a multi‐criteria decision‐aiding model capable of overcoming the two main difficulties related to preventive maintenance: establishing a replacement periodicity based on more than one criterion; and the ability to provide a solution even when failure data are unavailable or incomplete.

The purpose of this paper is to propose a supply chain risk management (SCRM) maturity model combined with a fuzzy TOPSIS classification method to evaluate and sort an organization into a pre-defined maturity level.

An axiomatic and prescriptive research method guided this study. Therefore, it proposes a prescriptive approach of maturity classification based on a theoretical SCRM maturity model combined with a multi-criteria decision technique.

The results of a pilot application indicated a consistent classification and the value of the model for diagnosing flaws and pointing directions for improving operational and disruption risk management. Its comprehensiveness allows applying it to supply chains of several industry sectors.

The proposed model does not include all possible risks and could be revised in further developments. Also, adjustment of the maturity profiles of the multi-criteria decision-making (MCDM) model requires a learning process from practical applications.

The adoption of the risk management maturity grid by practitioners may bring the benefit of a more objective and comprehensive evaluation of risk management processes in the supply chain context.

An immediate social implication derives from the improvement actions that may result from the diagnosis of risk management vulnerabilities identified in the pilot application. In general, the proposed model has the potential to reduce risks, improve results and contribute to economic sustainability.

The maturity grid and decision model integrate overall aspects of risk management, bringing together managerial concepts to deal with a variety of supply chain operational risks. The combined multi-criteria classification procedure to sort the maturity level of an organization is also a novelty.

The purpose of this paper is to develop a performance evaluation model for the operations of the supply chain of an organization of the refrigeration equipment sector. The tool must aid the decision maker in the performance improvement and creation of competitive advantages.

The study adopts a mixture of qualitative and quantitative approaches and applies them through a case study. The data collection was conducted through unstructured interviews and supplemented by documentary research. The applied intervention instrument is the Multicriteria Decision Aid – Constructivist (MCDA-C).

Identification, organization, ordinal and cardinal measurement and integration of the aspects of the context judged as relevant by the decision maker. In addition, it can be highlighted the current situation diagnosis and elaboration of improvement actions related to lean philosophy and advanced planning systems.

The developed model is being used to aid the decision maker in their decisions concerning the improvement of the supply chain operations.

The main contributions made by the paper resides in the proposal of solutions for fulfiling gaps identified within the supply chain performance evaluation area and in the application of the MCDA-C to a practical case.

Performance, Supply chain, Multicriteria, Decision, MCDA-C

Case study

Objetivo

El objetivo de este artículo es desarrollar un Modelo de Desempeño para las operaciones de cadena de suministro de una organización en el sector de equipos de refrigeración. La herramienta debe ayudar a quién toma las decisiones en mejorar el desempeño y crear ventajas competitivas.

El estudio usa una combinación de enfoques cualitativos y cuantitativos aplicándolos a un caso estudio. La recolección de datos se hizo a través de entrevistas no estructuradas y se complementó con investigación documental. El instrumento de intervención usado es el Multicriterio De Apoyo a la Decisión-Constructivista (MCDA-C).

Identificación, organización, mediciones ordinales y cardinales e integración de los aspectos de los contextos considerados como relevantes por el tomador de decisiones. Se puede destacar además la situación actual de diagnóstico y la elaboración de acciones de mejoramiento relacionados con la filosofía Lean y los Sistemas avanzados de planificación.

El modelo desarrollado esta siendo usado para ayudar al toma decisiones en las decisiones concernientes con el mejoramiento de las operaciones de la cadena de suministro.

La mayor contribución hecha por este artículo reside en proponer soluciones para cubrir brechas identificadas dentro el área de Evaluación de Rendimiento en la Cadena de Suministro y en la aplicación del MCDA-C a un caso práctico.

Desempeño, Cadena de Suministro, Decisión, Multicriterio, MCDA-C

estudio de caso

Objetivo

O objetivo de este artigo é desenvolver um Modelo de Avaliação Desempenho para as operações da cadeia de suprimentos de uma organização do setor de equipamentos de refrigeração. O modelo proposto deve ajudar o tomador de decisões a melhorar o desempenho e criar vantagens competitivas.

O estudo faz uso de uma abordagem qualitativa e quantitativa aplicada em um Estudo de Caso. A coleta dos dados foi feita por meio de entrevistas abertas, sendo complementada por pesquisa documental. O instrumento de intervenção usado é o Multicriteria Decision Aid – Constructivist (MCDA-C).

Identificação, organização, medições ordinais e cardinais, e integração dos aspectos do contexto são considerados como relevantes para o tomador de decisões. Além disso, destacam-se o diagnóstico da situação atual e a elaboração de ações de aperfeiçoamento, nas quais se avaliam os efeitos da implementação da Filosofia Enxuta e de um Sistema de Planejamento Avançado na organização.

O modelo desenvolvido auxilia o tomador de decisões nas decisões concernentes ao melhoramento das operações da cadeia de suprimentos.

As principais contribuições do artigo residem na proposição de melhorias em lacunas ainda presentes na avaliação do desempenho da cadeia de suprimentos e também na aplicação da MCDA-C em um caso prático.

Desempenho, Cadeia de Suprimentos, MCDA-C, Decisão, Multicritério

estudo de caso

The purpose of this paper is to propose a procedure to construct the membership functions for a one-unit repairable system, which has both active and standby redundancy. The coverage factor is the same for the operating and standby unit failure.

The α-cut approach is used to extract a family of conventional crisp intervals from the fuzzy repairable system for the desired system characteristics. This can be determined with a set of non-linear parametric programing using the membership functions.

When system characteristics are governed by the membership functions, more information is provided to use by management. On the other hand, fuzzy theory is applied for the redundant system; therefore, the results are more useful for designers and practitioners.

Different from other studies, the authors’ model provides more accurate estimation compared to uncertain environments based on fuzzy theory. The research would help managers and manufactures to make a better decision in order to have the optimal maintenance strategy based on the desired mean time to failure and availability of the systems.

The purpose of this study is to analyse the contribution of shifting the load of household devices from periods of renewable energy underproduction to surplus periods in order to better match energy production and demand.

An optimisation model for load shifting of household devices is developed and analysed with the help of a simulation of energy loads for the year 2030 in Germany.

About 1.48% of the renewable surplus energy can be used in addition which equals total savings between €15.06m and €106.71m. However, 24.47% of the surplus periods can be compensated completely and 6.38% up to a level of 94%.

A 100% diffusion of smart metres and devices and a high acceptance among consumers are assumed so that the results of this study present an upper bound for the contribution of household load shifting.

Load shifting of household devices provides only a small contribution and can only be one measure among others. It is crucial to find and invest in new energy storage systems so that more renewable spill-over energy can be used.

An optimisation model for load shifting is developed. Customer behaviour and devices are considered individually and not only a fixed percental share. Beside peak load periods also periods of renewable spill-over energy are considered.

The purpose of this paper is to propose a new three-phase switched reluctance motor (SRM), and achieve high-torque and low-cost. This new SRM's winding configuration uses the double-layer distributed windings, which is different from the conventional SRM's single tooth coils.

The operating principle of new SRM is analyzed, and the voltage equation and the generated torque are deduced. Finite element method (FEM) and finite element circuit coupled method are utilized to evaluate the new motor's operating performances. The two dimensional (2D) frequency response analysis model is employed in the FEM model. Based on the 2D frequency response analysis model, the magnetic field distribution, self-inductance, and mutual-inductance for the new SRM are analyzed in detail. A co-simulation model using FE analysis package and Matlab-Simulink is proposed to simulate the new SRM drive. The simulated and experimental results verify the new SRM.

For the new SRM with double-layer distributed windings, a co-simulation method is proposed to analyze its characteristics. The new SRM presents lower torque ripple coefficient and generates larger torque than the conventional SRM, with three-wire and standard full bridge power converter, rather than six-wire and asymmetric half-bridge converter for conventional SRM.

This paper proposes a new SRM with the double-layer distributed windings driven by a standard full bridge inverter. In order to calculate dynamic characteristics of the new SRM, a co-simulation method using FEM and Simulink is proposed to simulate the new SRM drive, where the power inverter and the current chopping control algorithm are implemented.

The paper aims to propose a multi-criteria model for risk prioritisation associated to supply chain management involving multiple decision-makers.

The model integrates the composition of probabilistic preferences (CPP) on the failure modes analysis and its effects (FMEA) criteria. First, the authors carried out a probabilistic transformation of the numerical evaluations of the multiple decision-makers on the FMEA criteria regarding the internal risks that affect the chain of clothing pole in the Agreste region of Pernambuco. Then, the authors proposed the use of the Kendall's concordance coefficient W to aggregate these evaluations.

Contrary to expectations, the two main risks to be investigated as a model suggestion was related to the context of supply chain suppliers and not related to the raw material costs. Besides, a simulation with the traditional FMEA was carried out, and comparing with the model result, the simulation is worth highlighting seven consistent differences along the two rankings.

The focus was restricted to the use of only internal chain risks.

The proposed model can contribute to the improvement of the decisions within organisations that make up the chains, thus guaranteeing a better quality in risk management.

Establishing a more effective representation of uncertain information related to traditional FMEA treatment involving multiple decision-makers means identifying in advance the potential risks, providing a better supply chain control.

Selecting and scheduling optimal project portfolio simultaneously is a complex decision-making problem faced by organizations to realize the strategy. However, dynamic synergy relationships among projects complicate this problem. This study aims at constructing a project portfolio selection and scheduling (PPSS) model while quantifying the dynamic synergetic effects to provide decision support for managing PPSS problems.

This study develops a mathematical model for PPSS with the objective of maximal project portfolio benefits (PPBs). To make the results align with the strategy, comprehensive PPBs are divided into financial and non-financial aspects based on the balanced scorecard. Then, synergy benefits evolve dynamically in the time horizon, and system dynamics is employed to quantify them. Lastly, a case example is conducted to verify the applicability of the proposed model.

The proposed model is an applicable model for PPSS while incorporating dynamic synergy. It can help project managers obtain the results that which project should be selected and when it should start while achieving optimal PPBs.

This study complements prior PPSS research in two aspects. First, financial and non-financial PPBs are designed as new criteria for PPSS, making the results follow the strategy. Second, this study illuminates the dynamic characteristic of synergy and quantifies the synergetic effect. The proposed model provides insights into managing a PPSS effectively.