Abstract in English:Abstract Paper aims This study analyzed the feasibility of the BiGRU-CNN artificial neural network as a forecasting tool for short-term electric load. This forecasting model can serve as a support tool related to decision-making by companies in the energy sector. Originality Despite a large amount of scientific research in this area, the literature still searches for more assertive forecasting models regarding short-term electric load. Thus, the BiGRU-CNN model, based on layers of BiGRU and CNN architecture networks was tested. This model was already proposed and used for other similar tasks, however, it has not been used on load forecasting. Research method The code was programmed in Python using the keras package. The forecasts of all networks were carried out 10 times until an acceptable statistical sample was reached so that future electric load values are as close as possible to reality. Main findings The best forecasting model was the proposed BiGRU-CNN network when compared to classical and some hybrid networks. Implications for theory and practice This methodology can be applied to short-term electric load forecasting problems. There is evidence that the combination of different layers of neural networks can provide more efficient forecasting results than classical networks with only one architecture.
Abstract in English:Abstract Paper aims The main objective of this article is to present and validate a method to integrate multiple management tools aiming for organizational excellence in medium and large enterprises. Originality There is a scarcity of methods to integrate management tools to support companies in their operations. This study aims to fill this gap, proposing a manner for companies to perform this integration. Research method The method was developed considering tools and concepts well-established in the literature, such as Lean Thinking, Six Sigma, Balanced ScoreCard, among other management tools. The mentioned method was validated through a survey with managers and directors who are experts in organizational strategies. They were carefully selected considering their professional background. Main findings The proposed method provides an alignment between strategy and execution, presenting a cyclical characteristic to be continuously reviewed method, considering market needs. The survey verified the adherence of the method and to conclude that it is a feasible alternative to reach organizational excellence. Although integration of management methods is fundamental for companies to reach organizational excellence status, this kind of guidelines is scarce in the literature. Implications for theory and practice This method can be used to increase companies’ performance and competitivity.
Abstract in English:Abstract Paper aims This paper studies a new Cross-Docking (CD) scheduling problem inspired by the trend of resource mutualization at CD operations where a company owning a CD platform can lease its docks to other companies. Originality This work pioneers the studies of the resource mutualization at CD operations solving at scheduling problem, where there is a set of requirements for leasing the loading and unloading docks for a period, and the company owning the docks can accept or decline each requirement. Considering that the availability of the docks is linked to scheduling the trucks at the company’s loading and unloading docks, the decision to accept the requirements must be made along with the decisions for scheduling the trucks. Research method To solve this problem, this work proposes a Mixed-Integer Linear Programming (MILP) formulation. Main findings Using a commercial solver, the MILP formulation can optimally solve 65/128 instances based on a real operation. For the remaining instances, the MILP formulation obtains an average optimized gap of 8.95%. Implications for theory and practice The MILP formulation obtains acceptable results. Moreover, we found that all the instances accepted the requirements showing that it is economically interesting to lease docks.
Abstract in English:Abstract Paper aims This paper studies the influence of process variation on deviation from nominal control chart performance and proposes some adjustments on the control limits to make it enable on small batches. Originality Specific methods were developed to monitor small batches, mainly due to unavailability of data for precise parameters estimation, like the deviation from nominal control charts. However, Montgomery (2014) highlights some essential aspects, such as the influence of process variation on its performance. Research method The method used was mathematical modeling and computer simulation. Main findings The results validated that there is a significant influence of the process variation on the control chart performance. It has been demonstrated that small adjustments on the control limits can make it enable on lean environments. Implications for theory and practice The main contribution is demonstrating the use of deviation from nominal control chart, through the valid control limits definition regardless of the samples size.
Abstract in English:Abstract Paper aims This study presents several business analytics tools that allow improving the tactical planning of the collection process for a Colombian solid-waste management company. Originality The extant literature of operations research/analytics applied to these systems focuses on facility location or vehicle routing. Tactical decisions are seldom studied in the operations research/analytics literature devoted to waste management systems. By contrast, the focus of this paper is on tactical decisions: fleet sizing, frequency assignment, route scheduling and internal resource allocation in a new waste transfer station. Research method We follow a multimethodology approach that uses mathematical programming, metaheuristics, and discrete event simulation. The models use historical information of the system, and the solution of a model are used as input data for the other models. Main findings Introducing a new waste transfer station allows an important reduction of the compactors fleet. However, to prevent a collapse in its internal operation an even operation is needed. This is achieved by rescheduling the routes to balance their arrival during the day. Additional benefits can be attained if some soft constraints are relaxed. Implications for theory and practice Practitioners looking for tactical planning tools on waste collection systems have here an example of their application and benefits. Improvements can be achieved by tactical planning without heavily disrupting decisions at the operational level.
Abstract in English:Abstract Paper aims Several Barriers impede the robust effectiveness of the supply-chain management implementation for the Malaysian automotive industry. The purpose of the present work is to identify these Barriers and prioritize them. Originality Originality of the present work lies in identifying the Barriers, putting them into categories and subsequently prioritize them by applying a scientific method such as Analytic Hierarchy Process (AHP).Research Research method This study has identified five main categories of Barriers through literature reviews. Fourteen practitioners who are involved with the automotive industry helped prioritise those Barriers by applying the AHP.Main Main findings Five main categories of Barriers are found to be technological, organisational, individual, strategic, and cultural barriers. Organisational barrier is the most critical barrier followed by technological and strategic barriers. Implications for theory and practice This research provides important feedback to the automotive company managers to take appropriate measures to minimise negative impacts of the barriers identified.
Abstract in English:Abstract Paper Aims This paper aims to develop an approach to support group decision making combining methods and tools to a holistic MCDA process. Originality Authors have been using Value-Focused Thinking (VFT) for structuring problems with different MCDA methods, but there is a lack of a process that defines a clear transition from VFT to those methods. Here we propose a process to fill this gap. Research method Rich Picture and VFT structure the problem and elicit objectives that become criteria within a decision hierarchy. Analytic Hierarchy Process (AHP) with ratings supports preference elicitation and sensitivity analysis in the judgment weights of decision-makers. Main findings VFT is effective for eliciting the decision structure to AHP; using weight distribution of stakeholders may affect the results, and the multimethodology approach developed here can deal with group decision making. Implications for theory and practice The approach developed is effective in complex environments (complex problems and multiple stakeholders) because it focuses on values and defines a process to bring those values into a multicriteria method. Furthermore, sensitivity analysis with the judgment weights of the different stakeholders may be useful in negotiation.
Abstract in English:Abstract Paper aims This study aims to analyze the relationship between the corporate social responsibility (CSR) strategy and competitiveness, considering the moderating effect of the governance mode on CSR actions. Originality This study sheds some light on a tendency towards the proactivity in terms of CSR of Brazilian Multinationals. They also present collaborative governance mode more frequently to conduct CSR actions. Research method In order to reach the research objective, a survey research was carried out in 144 Brazilian Multinationals and SmartPLS was used to conduct partial least square-structural equation modeling analysis. Main findings The results indicated that there is a positive relationship between CSR and competitiveness. Regarding the CSR governance mode, the adoption of different governance modes depending on the characteristics of the CSR action developed. Implications for theory and practice This paper contributes to the literature, since Latin America, especially Brazil, still lacks research that analyzes their CSR practices and establishes relationships with other organizational objectives, such as competitiveness.
Abstract in English:Abstract Paper aims This study aimed to analyze how the satisfaction level of public transport (PT) users is influenced by their socioeconomic characteristics. Originality The analysis of how socioeconomic variables influence the satisfaction level through the association between MANOVA and exploratory analysis is still not explored, especially in Brazil and in medium-sized cities, which represent the majority of Brazilian cities. Research method Data collection was carried out by questionnaire in a Brazilian city. The 330 users of PT evaluated their satisfaction level concerning 12 quality indicators. Statistical analyses were performed using Pearson's correlation and MANOVA. Main findings Most socioeconomic variables influenced user satisfaction in at least one indicator, gender and schooling being the most prominent. The results showed that women’s mean level of satisfaction is lower than men’s concerning indicators affected by gender. Fare was the indicator with the worst score, being influenced by users’ occupation. Implications for theory and practice The study presents practical and methodological contributions. The results provides technical and scientific subsidies for public policies and service improvement. It possible to improve each indicator according to the users’ socioeconomic characteristics, encouraging the use of PT and contributing to the urban environment sustainability.
Abstract in English:Abstract Paper aims Aiming to avoid an inefficient digital transformation, the present work proposes a framework that will provide companies with a strategy to implement technologies to legacy systems of maintenance. Originality Such a framework was produced through a series of strategic analyses using multicriteria decision-making (MCDM) methods. Research method These analyses are composed of three steps. First, reviewing the literature of industry 4.0 and interoperability, combining the RAMI4.0 architecture and Framework for Enterprise Interoperability (FEI). Second, by exploring technics of maturity assessments, addressing systems attributes and requirements. Third, reviewing the literature of Total Productive Maintenance (TPM) and recent maintenance technologies applications. Main findings The results confirm that such a framework can support the adequacy of legacy systems that are part of digital transformation projects. Implications for theory and practice To test the proposed framework, a multinational industrial entity belonging to the automotive sector was selected for a case study.
Abstract in English:Abstract Paper aims To define and evaluate the environmental performance of the implementation of reverse logistics (RL) for empty pesticide plastic containers (EPPC) in Brazil through the Campo Limpo System (CLS). Originality Discussion about the implementation of RL for the development of sustainable systems, through the identification of environmental impacts associated with RL of EPPC by means of Life Cycle Assessment (LCA). Research method CLS is described and used to quantify the potential environmental impacts of the RL chain of EPPC waste management by using the LCA methodology. The analysis comprehends the situations prior and post implementation of the CLS, it takes into account container manufacturing, transportation and end-of-life. Main findings Implementation of the CLS resulted in a reduction in nine assessed environmental impacts categories, ranging from a reduction of 79% to 26% in potential impacts. The stage leading to the largest contribution to environmental impacts is the manufacturing of EPPC. For end-of-life options, recycling proved to be the best option to lower environmental impacts. Implications for theory and practice Results show that the public policy was environmentally effective given that current activities in EPPC management led to lower environmental impacts enabling the development of a sustainable supply chain.
Abstract in English:Abstract Paper aims This research article addresses an innovative solution to face one of the main problems in the footwear industry, namely the high order non-fulfillment rate. Originality This research offers companies in the footwear industry the possibility of implementing Andon through a structured and planned process that allows expediting problem solving. The advantage of this system is the ability to signal the status of workstations through rapid visual identification. Moreover, in this way social distancing is also secured, in line with World Health Organization guidelines to prevent the spread of COVID-19. Research method The article presents four phases through which the case study was addressed. Planning (determination of objectives), Restructuring of the Operations Area, Improvement of the Production Line and Continuous Improvement. Main findings An Arena simulation system was used to establish a new scenario where the defective product indicator decreases by 3.13% and productivity improves by about 38%. In turn, the resulting increase in the number of orders enhances company sales and profits, as well as the ability to meet the customer demand in a timely manner. Implications for theory and practice The case study suggests that the main causes of this issue (high order non-fulfillment rate) are the increasing rate of defective goods, delays in the production process, and excessive time consumption in the movement of staff and materials. This research serves as the basis for future lines of research, as well as for other organizations with similar characteristics to implement the proposal.
Abstract in English:Abstract Paper aims the combination of the quality indices, a novel model called “Dynamic Growth Allocation Model (DGAM)”, Fuzzy Decision Making Theory (FDM), Analytical Hierarchy Process (AHP) and the Evolutive Particle Swarm Optimization (EPSO) is proposed. Originality the multi-objective optimization (with uncertainty) of the Argentine energy transition is not sufficiently studied. This combined methodology in this problem was not published and it had good, relatively easy and fast results. Research method the optimization indices (EROI, CO2, IC and RP), the methodology used (DGAM, FDM, AHP and EPSO) and its results are analyzed. Main findings (i) the nuclear energy allowed the renewable transition; (ii) the fossil dismantling and the investment in biomass and wind are needed; (iii) the EROI depends on the good load factor, useful life and performance. Implications for theory and practice It is sought a minimum Renewable Participation (RP) of 20% of Argentina with a sustainable energy matrix.
Abstract in English:Abstract Paper aims This research aims to analyze the primary studies published in recent years focusing on defect detection or classification in manufacturing and extract information about frequently used data mining (DM) methods, their accuracy, strengths, and limitations. Originality Industrial production is now undergoing a dynamic transformation in the context of Industry 4.0, where implementation of data mining is a frequently discussed topic, and such an overall summary is missing. Research method In this study, the PRISMA-driven systematic literature review is combined with the approach defined by Kitchenham (2004). Main findings The most frequently used data mining methods for defect detection are Bayesian network (BN) and Support vector machine (SVM). Besides previously mentioned methods, the Decision trees (DT) and Clustering are often used for defect classification. Neural Networks (NN) use is common for both defect detection and classification. DT, together with the Genetic algorithm (GA) and SVM, achieved the highest average accuracy. Recently, authors often combine different DM methods, and also methods for data dimensionality reduction are often used. Implications for theory and practice This study contributes to the quality management literature by extending a summary of recently used DM methods for defect detection and classification. This summary can help researchers choose a suitable method and build models for achieving its research purpose.
Abstract in English:Abstract Paper aims The present study aims to identify the limitations of the artifacts used in the decision-making process in the adoption of energy efficiency measures in productive systems, using non-intensive energy companies as a delimitation. Originality Identifies authors and connections, the relationships between them and how these interactions contribute to the advancement of knowledge on the subject. Regarding energy efficiency, studies show that the real investment in initiatives in the industrial sector is below the full potential and that the artifacts used in the decision-making process have severe limitations when used in a complex and dynamic context. Research method In this paper a systematic literature review was conducted from the Literature-Grounded Theory. Additionally, social network analysis was used. Main findings It concludes that the approaches are limited to technical and financial factors and does not consider a systemic and dynamic understanding of different internal and external variables to the organization. Implications for theory and practice The contribution of this study is that it identifies the initiatives that help in the process of decision-making for the adoption of energy efficiency measures in productive systems. Specifically, the focus of this study is on non-intensive energy companies. Scientific articles published in the main databases of management were selected.
Abstract in English:Abstract Paper aims To provide guidelines on current state of the literature on aspects related to the implementation of Industry 4.0 (I4.0) for operations flexibility in emerging economies, and derived from this, propose a conceptual framework for the analysis of the main topics studied. Originality Based on previous literature reviews on related topics (I4.0 and flexibility), we recognized an opportunity to focus on developing countries which until now has not been documented. Research method We carried out a systematic review of the literature together with a topic cluster analysis. Main findings The study revealed that there is a perceived consensus on how Industry 4.0 technologies can impact flexibility in emerging countries. Cloud computing is by far the most adopted technology despite the fact that there is a wide concern about security issues. The use of other technologies and their impact appears to be incipient. Implications for theory and practice The study presented here can be used as a starting point for new directions of research in terms of adoption of these technologies and new applications developed and/or customized to the realities of emerging countries.
Abstract in English:Abstract Paper aims Diagnostic analysis of PLM (Product Lifecycle Management) based on Industry 4.0 requirements supported by the AHP (Analytic Hierarchy Process) method. Originality The literature review found no research papers on PLM Maturity Models linked to requirements of Industry 4.0, attesting to the originality of the research and the topic proposed by the study. Research method The analysis is performed using an assessment framework that organizes and lists I4.0 attributes and PLM categories, supported by a multicriteria diagnostic assessment model based on the AHP method. The case study used in the research is an automotive industry located in the city of Curitiba, Brazil. Main findings A diagnostic analysis of the PLM categories and attributes of the I4.0 was performed, and the company’s overall levels of maturity were observed. Implication for theory and practice The results obtained from the diagnostic analysis indicate that the company maturity is Level 2, analyses were also undertaken with respect to PLM categories and Industry 4.0 attributes. Proposals for improvements were made with the objective of increasing the level of maturity and reducing gaps and problems identified in the diagnostic assessment.
Abstract in English:Abstract Paper aims The FMEA method (Failure Mode and Effects Analysis) has difficulty in prioritizing actions, verifying agreements among group participants and assessing uncertainty. This paper overcomes these shortcomings. The proposal applies FMEA in traditional format, establishes priorities for improvement actions, updates them periodically with better criteria than the traditional ones and values group agreement. Originality Other contributions claim to change the method, but this is not accepted by the organizations that apply it. In addition, they propose individual approaches, when the FMEA is essentially group-based. In contrast, this proposal establishes priorities without altering the basic requirements of the FMEA. Research method An action-research approach is used. Main findings Ease of application, improved group learning and commitment to action plans are confirmed. Implications for theory and practice A new group decision-making method is applied and a flexible solution is proposed, adaptable to very diverse problems.
Abstract in English:Abstract Paper aims This research develops an expert system for interoperable data acquirement and information enrichment in the manufacturing lines of a healthcare product, ensuring the correct data and information sharing and supporting the decision-making process. Originality The research contributes to creating and developing a novel method of knowledge representation that systematises the data collection and creates semantic relationships that allow the analysis of the productive performance of healthcare product manufacturing through semantic rules and inference engines. Research method The Interoperable Data Extraction and Information Enrichment system 4.0 (IDEIEs 4.0) was developed using an ontological approach and experimentally applied in an implantable Vascular Access Catheterindicated production process, which involves a machining controlling process. Main findings The developed system application pointed out the reduction of human mistakes in the data collecting, errors in the production control and data loss due to the digital automatic and interoperable collection process that brings precision in data collection and security in their storage. Implications for theory and practice The solution presented here can be used as a starting point for new directions of research to support the decision-making process with extra and formalised information, improving product quality, flexibilities the manufacturing process and reducing the time wasted.