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The textile industry is an important sector of the Brazilian economy, being considered the fifth largest textile industry in the world. To support further growth and development in this sector, this document proposes a process for production analysis through the use of Discrete Event Simulation (DES) and optimization through genetic algorithms. The focus is on production planning for weaving processes and optimization to help make decisions about batch sizing and production scheduling activities. In addition, the correlations between some current technological trends and their implications for the textile industry are also highlighted. Another important contribution of this study is to detail the use of the commercial software Tecnomatix Plant Simulation 13®, to simulate and optimize a production problem by applying genetic algorithms with real production data.

Goal: The purpose of this paper is to present a proposal of steps for the implementation of Industry 4.0 in the industrial context, considering management and operational aspects. The reason is to discuss that technological change is accompanied by many organizational implications, in which it is perceivable that some companies already experience strategic and operational turbulence due to the lack of understanding of the this structure’s complexity. Design / Methodology / Approach: This study assumes an exploratory character because the subject of analysis is still in the knowledge-structuring phase. In this sense, data was collected from the literature review. Results: A theoretical proposal for the Industry 4.0 implementation framework is presented in flow format. It is organized in steps that cover the strategic and operational aspects during the implementation flow. Limitations of the investigation: The limitations of this study are directly related to its theoretical nature and the difficulty of finding tools that help in the execution of each proposed stage. Practical implications: However, based on theoretical insights, a trajectory of a transformation model is proposed, thus this research intends to show clearly and direct how companies can introduce the aspects of Industry 4.0 to their own benefit. Originality / Value: In this study, a conceptual model is structured, and it indicates a potential of application because it contributes to support and encourage the adoption of technologies and concepts indicated in the Industry 4.0 literature in a structured way.

The main objective of this exploratory research was to develop and validate a model to measure the maturity of manufacturing cells that operate according to the lean philosophy. A theoretical model was constructed based on parameters from the literature and information provided by a panel of experts. Using a questionnaire based on this theoretical model, a survey of 101 cell managers was carried out and the data collected were analyzed by partial least squares structural equation modeling (PLS-SEM). The results show that the maturity of a manufacturing cell can be measured using the three constructs ‘Employee Knowledge and Skills’, ‘Quality and Continuous Improvement’ and ‘Cell Configuration’. Of these, the second had the greatest impact on cell maturity. The results also show that a fourth construct, ‘Leadership, Autonomy and Communication’, influences maturity indirectly. These findings may be used by managers of manufacturing cells and by researchers.

Recently the technological evolution resulting from the fourth industrial revolution, especially with the advancement of the internet of things and bigdata, coupled with the change in consumer behavior, are forcing companies to improve the efficiency of production systems. Now, companies must mass produce to keep costs low, but they must also be flexible and offer a wide variety of products. Thus, companies are increasingly using computational tools to improve decision making, especially with the application of simulation and digitization of production systems. However, online data collection is presenting itself as a solution to decrease the time for the development of simulation models and, thus, speed up decision making. In this way, this work shows the steps required for online data exchange between a real system and a virtual production system. For this, a prototype will be used that demonstrates these basic concepts.

In 2016, the Brazilian pet industry had revenue of R$ 18.9 billion and ranked third place worldwide. Thus, it is a sector that is always looking for enhancements in its productivity levels. Based on the previous statements, a case study was conducted in a selected company of the pet care business, with the goal to augment its monthly revenue, identify the bottleneck that impedes reaching this goal, and proposed solutions to bring the production and loading fluxes of merchandise to its optimal state, making the company’s revenue also optimal. The classical tools of the theory of constraints were used in this analysis. The first step was to obtain the undesirable effects of the process to define the bottleneck. After that, some injections were proposed as solutions to eliminate the undesirable effects and bring the production and loading model of the company to its full state. Finally, by means of a computational tool, the current situation of the company (with the bottleneck), and the situation in a virtual state (without the bottleneck) were simulated and compared, showing the potential of the found solution.

The purpose of this paper is to analyse the integration of discrete event simulation (DES) in operations management manufacturing tools. Due to the movement of the fourth industrial revolution (Industrie 4.0), the integration of manufacturing is a topic constantly discussed in many areas. Moreover, it presents great research and innovation opportunities. To achieve the objective of this study, a search was conducted using the main keywords found in papers related to manufacturing systems and operations management manufacturing tools. Also, academic databases were literature research to identify the keywords relevant to the study added to DES. We considered only articles from the last 8 years. At the end between the search, the integration between tools such as manufacturing execution system, enterprise resource planning, radio frequency identification, core manufacturing simulation data, e-Kanban with DES were analysed. Furthermore, it was observed that the tools cannot always be used separately, but in some cases, these tools should be used jointly to solve problems related to production systems. Another aspect observed was how the data collected in production systems are fed to the DES models. Through, it was possible to analyse an existing gap regarding how the data is used between DES and manufacturing systems, thereby enabling research development in this area.

In 1997, Eliyahu Goldratt proposed a method called Critical Chain Project Management (CCPM) to minimize the inefficiencies identified in traditional project management. The project management community accepted the proposed method as a viable alternative. However, to allow its implementation with a multiproject system, more research was necessary. Seeking to identify the key factors that influence the performance of the multiproject system applying the CCPM method, we performed a case study. Logistic regression analysis showed that applying the CCPM method in a multiproject system allows for better time estimation of activities and facilitates the allocation of critical resources. This work was supported by the São Paulo Research Foundation (FAPESP) under Grant number 2015/21324-4. info:eu-repo/semantics/publishedVersion

Highlights: The product development methodology aims to assist the planning and design of the product throughout its life cycle. Using selection criteria it is possible to choose a solution will be followed until the end of the development process and this process is known as optimization of product solutions. Design for Manufacturing and Assembly (DFMA) is an approach that allows selecting a product solution with better manufacturing and assembly performance. Computational modeling allows representing systems in virtual environment in order to reproduce its characteristics and to compare scenarios through simulation. Goal: The objective of this work was to apply the computer simulation to compare the productive performance, according to production times, productivity and resource utilization rate, of three solutions proposed for a raincoat for pets with thermal protection. Methodology: Initially, conceptual models representing the production systems for the three product solutions were generated. The systems were modeled in discrete event simulation software, enabling different scenarios testing, resulting in production performance indicators for each product solution. Results: The analysis of the performance indicators allow identifying that the third solution proposed for the product obtained the best productive performance in all proposed scenarios; therefore, it was chosen as the best solution for the product according to the DFMA approach. Limitations of the investigation: The application of the methodology indicated in this work was limited to the study of a single productive system of a specific product. Practical implications: This work presents a practical application of computer simulation tools applied to product development. Originality / Value: The original contribution of this work is the application of computational simulation of production systems in product development following the DFMA approach.

This study shows the contribution of Discrete Event Simulation (DES) for improvement of statics production scheduling process in the environment of dynamic demand. Using simulation software - Tecnomatix Plant Simulation 13 ® by Siemens, makes it possible to structure a digital factory model. It defines and validates the operating logic of this model and enables the automatic reconfiguration of production planning. This virtual model represents the operations of eyewear industry starting from placing customer request till collecting final product. The primary purpose is to automate most of the production planning process and enable automatic execution in virtual settings, which will potentially guide the physical operation. The result is to provoke integration between production management systems with simulation tools, therefore increase productivity, reduce waste and improve the use of labor.