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Production management serves as a pivotal component in the operational activities of oilfield sites, with the effectiveness of management practices directly influencing the success of developmental outcomes. To enhance the maintenance-free operational period of oil production systems, elevate management standards, and reduce overall operational costs, advanced technologies such as artificial intelligence (AI) and big data analytics have been strategically integrated into oilfield operations. These technologies are able to incorporate data resources from all stages of oilfield production, thus providing a comprehensive view of oilfield production and guidance for production. This study uses a series of diagnostic and predictive methods to construct a management system that allows for the comprehensive monitoring and fault diagnosis of oil production systems, which can ensure the intelligent management of oil production systems at multiple levels throughout their life cycle. Automated monitoring workflows and proactive analytical processes are at the heart of the framework, enabling real-time monitoring and predictive decision-making. This not only minimizes the likelihood of system failure but also optimizes resource allocation and operational efficiency. [ABSTRACT FROM AUTHOR]

A healthy lifestyle encourages people to regularly eat more fruits and nuts, including nutritious snack bars, which provide excellent nutritional and energy value and are exceptional convenience foods with the necessary content of macro- and microelements, dietary fibre and biologically active compounds. The article analyses and proves the usefulness of fruits and nuts, which have a positive impact on human health in snack bars. The consumption of nuts demonstrates a positive effect on health, preventing and/or creating a therapeutic effect on a person by reducing some risk factors associated with chronic diseases. The simulation, which reflects the structure of the population's diet, when all snacks between meals, with the exception of drinks, were replaced by nuts, records a significant decrease in added sugar (-17.8 %), solid fats (-21.0 %), saturated fat (-6.6 %) and sodium (-12.3 %), and an increase in monounsaturated (+35.4 %) and polyunsaturated fats (+42.0 %), vegetable omega-3 fatty acids (+53.1 %), dietary fibre (+11.1 %), magnesium (+29.9 %) and a slight increase in potassium (+1.5 %). The available scientific evidence shows that nut consumption (15 to 30 g per week for 3 to 16 weeks) does not provide additional health benefits for children aged 8 to 18 years, but replacing high-calorie, low-nutrient snacks with nuts can help to promote healthy dietary habits as children grow into adults. A survey of 188 respondents (39.3 % male, 60.7 % female) was conducted to investigate the attitudes of Ukrainian youth towards nut consumption and preferences for snack bar flavours. While protein bars can be considered a speciality food for consumers seeking to increase muscle mass, snack bars based on nuts and dried fruits are seen as snacks with an overall positive impact on the body. When eating, a person has a certain sequence of chemosensory sensations that influence the aesthetic pleasure of eating certain dishes, and the taste preferences of respondents show that the most desirable aroma and taste is chocolate (39.3 %), followed by hazelnut (32.8 %) and strawberry (13.1 %). The least desirable flavours for consumers are blueberry (2.6 %), cereal (2.0 %) and banana (2.0 %). In addition to attention to the vitamin content (44.3 %), respondents are interested in the absence of chemical additives (27.9 %) and sugar (16.4 %) in snack bars. Despite the scientifically proven positive effects of antioxidants and dietary fibre on the human body, only 1.6 % of respondents consider their presence to be a determining factor in choosing a food product. Based on the study conducted by the authors, it was found that using a mixture of nuts and dried fruit for snacking creates a balance between monounsaturated and polyunsaturated fatty acids, provides the body with essential vitamins and is desirable for consumption. Snack bars containing nuts and dried fruits are organoleptically the most desirable for consumers and may be useful in preventing a number of diseases. This study can be used to make managerial decisions in the production of healthy food products.

The paper presents a novel MCDM model aimed at enhancing satisfactory quality-environmental decisions in product development. The model integrates FAHP, FTOPSIS, Pareto-Lorenz and global sensitivity analyses. It enables to study products with respect to quality level, environmental impact throughout its life cycle and simultaneous consideration on quality level and environmental impact. Results of the research on the example of a smartphone demonstrate that the model successfully identified specific criteria for improvement, offering a valuable tool for enhancing customer satisfaction and promoting environmentally friendly product development. The originality of the research lies in the calculation of the average weights of product criteria with triangular fuzzy numbers, based on the principles of fuzzy logic and FAHP. As a compact, ready-to-use solution, our innovative MCDM model can be employed by organizations to enhance the quality and environmental impact of their products. [ABSTRACT FROM AUTHOR]

Research background: Generative artificial intelligence (AI) and machine learning algorithms support industrial Internet of Things (IoT)-based big data and enterprise asset management in multiphysics simulation environments by industrial big data processing, modeling, and monitoring, enabling business organizational and managerial practices. Machine learning-based decision support and edge generative AI sensing systems can reduce persistent labor shortages and job vacancies and power productivity growth and labor market dynamics, shaping career pathways and facilitating occupational transitions by skill gap identification and laborintensive manufacturing job automation by path planning and spatial cognition algorithms, furthering theoretical implications for management sciences. Generative AI fintech, machine learning algorithms, and behavioral analytics can assist multi-layered payment and transaction processing screening with regard to authorized push payment, account takeover, and synthetic identity frauds, flagging suspicious activities and combating economic crimes by rigorous verification processes. Purpose of the article: We show that edge device management functionalities of cloud industrial IoT and virtual robotic simulation technologies configure plant production and route planning processes across cyber-physical production and industrial automation systems in multi-cloud immersive 3D environments, leading to tangible business outcomes by reinforcement learning and convolutional neural networks. Labor-augmenting automation and generative AI technologies can impact employment participation, increase wage and wealth inequality, and lead to potential job displacement and massive labor market disruptions. The deep learning capabilities of generative AI fintech in terms of adaptive behavioral analytics and credit scoring mechanisms can enhance financial transaction behaviors and algorithmic trading returns, identify fraudulent payment transactions swiftly, and improve financial forecasts, leading to customized investment recommendations and well-informed financial decisions. Methods: Machine learning-based study selection process and text mining systematic review management software and tools leveraged include Abstrackr, CADIMA, Colandr, DistillerSR, EPPI-Reviewer, JBI SUMARI, METAGEAR package for R, SluRp, and SWIFT-Active Screener. Such reference management systems are harnessed for methodologically rigorous evidence synthesis, study selection and characteristic extraction, predictive document classification, machine learning-based citation and record screening, bias assessment, article retrieval automation, and document classification and prioritization. Findings & value added: Industrial IoT and 3D augmented reality technologies can create business value by streamlining virtual product and remote asset management across extended reality-based navigation and robotic autonomous systems in smart factory environments by generative AI and machine learning algorithms, articulating business organizational level and theory of management implications. 3D simulation and operational modeling tools can execute and complete complex cognitive task-oriented and knowledge economy jobs, producing first-rate quality outputs swiftly while leading to unemployment spells, labor market disruptions, job displacement losses, and reduced earnings by machine learning clustering and spatial cognition algorithms. Generative AI decentralized finance, interoperable blockchain networks, cash flow management tools, and asset tokenization can mitigate fraud risks, enable digital fund and crypto investing servicing, and automate treasury operations by integrating real-time payment capabilities, routing and configurable workflows, and lending and payment technologies. [ABSTRACT FROM AUTHOR]

Agricultural business methods are no longer possible without computer technology, which helps to identify animals, record productivity and monitor their health. Therefore, the study aims to conduct a comparative analysis of the functionality of the main dairy farm management software for their objective assessment from the point of view of milk producers. For this purpose, information from the official websites of software products was analysed and scientific articles analysing this software were collected. As a result, all software products were divided into 3 categories: software for controlling dairy productivity and managing processes on a dairy farm from dairy equipment manufacturers; such software products include DairyPlan C21 (GEA), DATAFLOW II (Milkline), AfiFarm (Afimilk), DelPro (DeLaval) and FARMSOFT (Farmtec a. s.); dairy farm management software DairyComp 305 and UNIFORM-Agri, as well as farm software from post-Soviet developers – MilkCentre (CIAB Expert). Programmes from dairy equipment manufacturers were almost at the same level and had virtually all the necessary blocks for identifying, controlling and managing animals on a dairy farm. The software developed for dairy farm management is more effective in tandem with one of the milking parlour programmes. This class of software expands the possibilities for managing reproductive and veterinary work on the farm, as well as reduces the workload on staff by generating automatic reports for regulatory authorities and management. The third class of programs is the least developed compared to the above, but it compensates for this shortcoming by constant improvement due to the continuous contact of developers with the manufacturer. Thus, there is a significant number of software products on the software market that can provide dairy management for farms of various sizes

The article analyses the role of immersive technologies in increasing productivity in enterprises. Economic growth is determined not only by productive forces, but also by the rational use of human labour and achievements of scientific and technological progress. The author has examined the experience of using digital tools relevant to the market that improve productivity – virtual and augmented reality. These technologies have a significant impact on labour productivity and contribute to enhancing performance indicators of production operations. The global practice of applying immersive technologies in enterprises demonstrates a wide range of areas of their use. Thus, augmented and virtual reality are in demand in mechanical engineering, energy extraction, logistics, design of facilities and production lines. In essence, these technologies expand the boundaries of human capabilities in interaction with virtual and augmented spaces, providing unique management tools for solving tasks of varying complexity, and have significant potential in the context of better productivity. Based on the results of the analysis, the key functions of augmented and virtual reality in industry have been identified, and the structure of the functional usage of immersive technologies to increase productivity has been developed.

Copyright of Signos is the property of Universidad Santo Tomas and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Organizations increasingly recognize the need to act in accordance with the idea of sustainable development. In the context of a production system, this is based not only on minimizing material losses but also on human support in the work process. The activities described in this article verify the operation of the system by collecting data on problems occurring during the production process, and the presented case study shows not only that companies do not always have to base their analyses on expensive solutions constructed on big data but they also misinterpret the causes of disruptions, which leads to further losses. This study presents an innovative system supporting the identification of downtime, and the results obtained allowed the examined organization to introduce changes based on specific premises, which led to reducing the waste of resources. The research carried out showed that it is not the excessive load on machines that is the problem but unnecessary downtime resulting from, for example, poor-quality materials for packaging goods. [ABSTRACT FROM AUTHOR]

Agricultural business methods are no longer possible without computer technology, which helps to identify animals, record productivity and monitor their health. Therefore, the study aims to conduct a comparative analysis of the functionality of the main dairy farm management software for their objective assessment from the point of view of milk producers. For this purpose, information from the official websites of software products was analysed and scientific articles analysing this software were collected. As a result, all software products were divided into 3 categories: software for controlling dairy productivity and managing processes on a dairy farm from dairy equipment manufacturers; such software products include DairyPlan C21 (GEA), DATAFLOW II (Milkline), AfiFarm (Afimilk), DelPro (DeLaval) and FARMSOFT (Farmtec a. s.); dairy farm management software DairyComp 305 and UNIFORM-Agri, as well as farm software from post-Soviet developers - MilkCentre (CIAB Expert). Programmes from dairy equipment manufacturers were almost at the same level and had virtually all the necessary blocks for identifying, controlling and managing animals on a dairy farm. The software developed for dairy farm management is more effective in tandem with one of the milking parlour programmes. This class of software expands the possibilities for managing reproductive and veterinary work on the farm, as well as reduces the workload on staff by generating automatic reports for regulatory authorities and management. The third class of programs is the least developed compared to the above, but it compensates for this shortcoming by constant improvement due to the continuous contact of developers with the manufacturer. Thus, there is a significant number of software products on the software market that can provide dairy management for farms of various sizes. [ABSTRACT FROM AUTHOR]

Palm trees are one of the potential commodities to be developed in Indonesia, one of which is in Rambah Tengah Hulu Village, Rambah District, Rokan Hulu Regency. Usually, craftsmen process palm water into molded palm sugar. The survey results show that 16 palm sugar craftsmen in Rambah Tengah Hulu Village have joined the palm sugar craftsmen group. It's just that this group has not been active for a long time. The main problems found among palm sugar craftsmen are that the production process of processing palm sap into palm sugar still uses very simple technology, the size of the product produced is not yet uniform, and palm sugar craftsmen have never received training or counseling regarding management, planning and recording business finances, so it is necessary Efforts are made so that groups of palm sugar craftsmen can maximize their business development. The aim of implementing this service is to provide solutions in improving technology and management of palm sugar business production. The method for implementing this service is that first the craftsmen are given counseling about the importance of forming a group in a business, then the craftsmen are given counseling about financial planning and recording. Craftsmen also make furnaces and tools for molding palm sugar and are given assistance in using and maintaining them. The result of this community service activity is that the average understanding of partners about the importance of group formation, planning and recording finances has reached 77.95%. Craftsmen understand the use of applied technology and craftsmen understand planning and recording business finances, as can be seen from the increased understanding of participants before and after carrying out activities. Craftsmen also have uniform printing equipment and modified furnaces.Technology; production management; Palm sugar

The paper aims to show the possibilities of using modern information technologies in production management. Successive stages of production process preparation and implementation are characterized. Information technologies that are currently being implemented in manufacturing enterprises are discussed. The focus was on the part of the process related to the product's manufacture. The paper presents the concepts of two methodological approaches to the adoption of modern information technologies: the top-down approach and the bottom-up approach. The successive stages of each of these approaches are discussed. The advantage of the top-down approach is the ability to comprehensively implement various technologies, and the disadvantage is the significant level of resource commitment. The advantage of the bottom-up approach is the high efficiency of the proposed solution, and the disadvantage is the limitation of application to projects of limited size. The proposed approaches have been verified using the example of two companies: the automotive and the control automation industries. There are correlations between the choice of the methodology used and the type and extent of implementation of the technology in question. The study's key conclusion is that both approaches are applicable in practice. The most important thing in the decision-making phase is to identify the barriers and constraints related to the organization's maturity to use a given technology. Enterprises can use the study results to help them prepare for their digital transformation.

In a manufacturing environment the effectiveness of internal problem solving is a key success factor in the service level performance offered to the customers. Broken internal processes need to be fixed immediately or at least in a very short time, in order to fulfill the committed delivery dates. There are several methodologies applied for internal problem solving used by different companies. This article presents a solution worked out for a plant operating in a high-mix low-volume (HMLV) production environment prone to both internal and external disruptions and disturbances. Principles, architecture and information flow in our digitized disruption handling -- so-called escalation -- system will be shortly discussed. Lessons learned in a six-year's period of using the system will also be summarized. The recorded data confirm that with the introduction of the escalation system the capability of the plant to adapt to changing circumstances and disruptions greatly improved. [ABSTRACT FROM AUTHOR]

This paper aims to develop an integrated Quality–Cost–Environmental (QCE) indicator for the selection of photovoltaic panels (PVps) offered to customers, considering the following criteria: (i) quality satisfaction; (ii) cost-effectiveness; and (iii) environmental impact throughout the life cycle. The proposed QCE indicator was developed within a framework that incorporated an FAHP (Fuzzy Analytic Hierarchy Process), cost-effectiveness analysis (CEA), and life cycle assessment (LCA). The model test confirmed its effectiveness in choosing a PVp which combines environmental friendliness throughout its entire life cycle with satisfactory quality and a reasonable purchase price for customers. The proposed model can be utilized by individuals, businesses, and public entities for the selection of high-quality, cost-efficient, and environmentally friendly PVps—thereby promoting sustainable development. [ABSTRACT FROM AUTHOR]

This research examines the production management of self-propelled mortar carrier systems in supporting the independence of Indonesia's defense industry. In accordance with the Law of the Republic of Indonesia No. 16 of 2012 on Defense Industry which aims to ensure that the fulfillment of defense and security equipment can be carried out independently. This research uses the theory of production and production management presented by E.L. Brech. The production system starts from inputs, which consist of information, management, equipment and workers, as well as raw materials and capital, which then get treatment in the form of transformation into outputs in the form of goods and services. This research uses a qualitative research method with a case study approach. Primary data is obtained through interviews and direct observation to related parties, while secondary data is obtained from literature studies, documents and other data. This research reveals that the production process at PT SAS Aero Sishan still requires improvement efforts to increase production effectiveness. This research underlines the importance of production management to optimize the resources owned through the production process so as to produce quality and superior products and services in order to realize the independence of the defense industry.

Production companies’ ambition to reach sustainable development goals, has resulted in a rapid strategic movement towards circularity in production. Previous studies have indicated that a transition to circular production is affirmed and a prioritised action. However, few studies describe how to operate a circular production, and how to perform the transition from linear to circular. To fill this gap, this paper aims to explore strategies for a seamless transition and to add new knowledge in this area. A multiple case study was employed for this purpose, based on production companies located in Sweden. Collected data were analysed by an inductive coding process. The coding process generated managerial themes that characterise the transition process in production operations. From the themes, three main incubators: management systems, standards and strategy, form together with drivers and blockers a framework called Integrated Circularity Management Systems (ICMS). The research presented in this study adds new knowledge to the field of circular production operations management as well as gives practical guidance for decision-makers in the manufacturing industry on how to initiate a circularity transition in an established production system.

This community service aims to increase the understanding and skills of Jamu Larasati partners in managing production, digital marketing, financial management, and business financial reports. The method for implementing this service used training and FGD. The instrument for evaluating this activity used practice sheets and was analyzed descriptively. The results of this service showed that partners' understanding and skills in production management, digital marketing, and financial management have increased. It was proven by partners who had increased production quantity from 100 bottles per day to 120-150 bottles per day. Partners also had abilities related to digital marketing, proven by partners having the ability to use SEO and create marketing content that suits their business. Apart from that, partners also had financial management skills, as proven by partners having financial reports and being able to analyze the results of financial reports.

The primary objective of this study is to examine the connection between Generation Z Indonesian consumers’ perceptions of value for green products and their purchase intentions, with a supplementary investigation into how environmental concerns moderate the influence of perceived green value on their intention to purchase green products. Between June and December 2021, a probability sampling technique, specifically stratified random sampling, was used to select a sample of 543 Indonesian Generation Z consumers. The data were analyzed using a variance-based method, namely partial least squares, within the context of structural equation modeling. The analysis reveals that functional value, conditional value, and environmental concern significantly and positively affect the intention to purchase green products. This indicates that Generation Z consumers are more inclined to choose green products when they perceive them to have good functional value, when specific conditions or requirements support the purchase, and when they have a high environmental concern. Moreover, environmental concern moderates the effect of social value on the intention to purchase green products. This suggests that more environmentally conscious consumers are more likely to be influenced by social value benefits when deciding to buy green products, highlighting the complex interplay between environmental and social motivations in shaping consumer behavior towards sustainability.

The concept of competitive advantage serves as a guiding principle for establishments within the food processing industry as they strive to attain high quality standards. The pursuit of a competitive economy aligns with Egypt's Vision 2030, aimed at fostering economic growth through digital transformation. Developing strategies to enhance the competitive edge of food sector products is of paramount importance. The findings revealed that the average value of food industry products reached approximately 12.99 billion Egyptian pounds between 2000 and 2020, constituting about 1.36% of the domestic product. This sector exhibited an annual growth rate of 3.90%. Furthermore, the performance of the food sector is positively influenced by effective leadership and superior quality. Among the factors analyzed, motivation and technology, followed by responsiveness, accounted for about 32.16%, 14.28%, and 13.68% of the positive impact, respectively. Strategic planning and leadership accomplishments were also identified as positive contributors. Innovation, development, and strategic orientation explained around 26.90%, 19.62%, and 14.74% of the impact, respectively. Operational management practices play a favorable role in enhancing production flexibility and managing uncertainties. They contribute approximately 22.85%, 21.19%, and 20.28% of the overall effect. Supply chain management was another area with a positive influence. Contracting, followed by supply flexibility and electronic supply, exhibited impacts of roughly 27.72%, 22.11%, and 12.39%, respectively. Effective management of marketing services showcased positive effects as well. The foremost impact came from marketing services, marketing flexibility, and marketing strategies, contributing around 23.17%, 20.43%, and 17.99%, respectively.

Manufacturing companies characterized by high-mix and low-volume production exhibit distinct features that exert a significant influence on the product introduction process. The quality of information exchange between product design and production interfaces becomes paramount in low-volume manufacturing. Consequently, there is a pressing need to explore various methods for adapting and customizing management strategies to align with the unique characteristics of low-volume manufacturing and its associated product introduction processes. Although this knowledge is critical in low-volume manufacturing, most existing studies focus on the management aspects of high-volume manufacturing. Therefore, this study investigated the customization of management strategies for product introduction in low-volume manufacturing to enhance the quality of information content. Drawing upon a longitudinal analysis of new product introductions within a low-volume manufacturing company, this study identified four management strategies—namely, securing a production test and verification plan, revising the role of product introduction management, developing a formal design and production coordination plan, and developing lessons learned management plan. The paper explains how the examined company adapted and implemented product introduction management strategies to facilitate the enhancement of information content quality across three key stages: pre-implementation, post-implementation, and subsequent modification and refinement of strategies following the initial round of implementation. By shedding light on these strategies, this study offers a comprehensive understanding of management approaches for product introduction in low-volume manufacturing. The study makes a valuable contribution to the discourse on information quality management and design-production interface in the low-volume manufacturing and low-volume product introduction literature. [ABSTRACT FROM AUTHOR]

Over the years, the integration of Production Management and Maintenance Management has gained significant attention from the scientific community due to its benefits for the company. When searching through the states of the art and practice, it is possible to understand that one of the main challenges for the integration is the lack of systematic, methodological, and scientific approaches and evaluation systems that lead companies into a successful implementation and a clear understanding of the benefits and drawbacks of the process. This paper introduces an original framework that conducts the processes of evaluation, weighting, and aggregation of set of novel indicators proposed by the authors. The main output of the proposal is an integral index that allows us to qualify, in a linguistic domain, the importance of the Production and Maintenance Management integration. At the same time, the proposed framework includes a methodology to evaluate the consensus of the experts, based on the use of linguistic terms with a membership function of the triangular type, which attempts to overcome some deficiencies of previous models identified by the authors in a detailed and complex analysis of the scientific literature. The proposed framework is applied in a plant of the Cuban mechanical industry. The results of this application are clearly presented and discussed, allowing us to verify and validate the proposal while also contributing to its ease of understanding and ultimately to the successful integration of the production and maintenance tasks in the given company. [ABSTRACT FROM AUTHOR]

Copyright of Opuntia Brava is the property of Universidad de Ciencias Pedagogicas de Las Tunas, Centro de Documentacion e Informacion Pedagogica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In today’s competitive world, uncertainty is an integral part of all optimization problems. One of the cases where uncertainty has the greatest impact on optimization issues is SCN design. In most of the conducted studies, parameters such as demand, transportation cost and capacity of tehsils have been published in an uncertain manner. In this type of problem, various methods have been used to control these uncertainty parameters, which can be referred to as fuzzy programming, robust optimization, two-stage stochastic programming, multi-stage stochastic programming, multi-stage fuzzy stochastic programming, fuzzy robust optimization. Each of the mentioned methods has limitations in terms of its implementation. in the fuzzy programming method, there is no deviation from the data collected by experts’ opinions. In probabilistic methods, it is very difficult to determine the exact type of distribution function. Therefore, many researchers have investigated the strengths and weaknesses of each method in their studies. Therefore, in this paper we try to review the strength and weakness of these methods to apply the best approaches for different situations. In this paper, a real-world case study of a natural gas supply chain is investigated. By using concepts related to natural gas industry and the relations among the components of transmission and distribution network, a Five-level supply chain has been introduced and presented schematically.

This data article presents a dataset obtained from a national survey of African catfish production in Nigeria. The African catfish is an important aquaculture species in various regions in the world and it is, after Tilapia, the most commonly cultured fish in Africa. Nigeria's share in the global production of African catfish exceeds 67 %. The dataset encompasses data collected from ten major catfish-producing states in Nigeria, with a focus on two distinct periods: before and during the COVID-19 pandemic. A total of 609 operations were captured for the pre-COVID and 509 for the COVID period. The dataset includes a wide array of variables, covering the cost and quantities of inputs and outputs, socioeconomic factors, market dynamics, feed types, challenges faced by farmers, scale of production, and farmers' level of experience. It offers valuable insights and opportunities for various stakeholders. Researchers can utilize it to explore production performance, resilience, and adaptation strategies. Industry players, including catfish farmers and suppliers, can make data-driven decisions to enhance their operations. Policymakers can formulate evidence-based policies to support sustainable growth in the catfish farming sector. Other developing countries can draw lessons from Nigeria's experiences to bolster their aquaculture sectors.

Abstract Over the last years, pharmaceutical industries have adopted continuous improvement and operational excellence programs to optimize processes, improve quality and reduce operational costs. Worldwide, Lean Manufacturing (LM) and Six Sigma (SS), as well as the integration of the two methods: Lean Six Sigma (LSS) are the most used approaches in the continuous improvement of industries and services. This work aims to investigate the employment of the Lean Six Sigma methodology in the productive areas of pharmaceutical companies located in Brazil. Interviews were conducted with managers of pharmaceutical industries that apply the approach. The results indicated the greater use of Lean Manufacturing tools compared to Six Sigma and the influence of specific peculiarities of the pharmaceutical industry on the benefits that are achieved with the use of Lean Six Sigma. The approach is considered of great value as it provides substantial benefits to the pharmaceutical industry. It is concluded that the work corroborates to the theoretical and empirical knowledge about the methodology use in the context of Brazilian pharmaceutical industries, as well as contributes to the implementation, reformulation, and improvement of Lean Six Sigma programs in this industrial segment.

The need to integrate competences aligned with the Sustainable Development Goals (SDGs) into higher education curricula has gained considerable attention in recent years. While the literature shows an increase in research on this topic, there remains a scarcity of papers addressing effective strategies to foster students' environmental sustainability competencies and skills, through active pedagogical methods. A promising avenue to achieve this goal is the adoption of the Flipped Classroom methodology. This approach has proven its ability to guide students towards reflection and critical thinking, making it a good tool for promoting sustainability awareness. An experience of educational innovation is presented that develops SDG 12 "Guarantee sustainable consumption and production patterns", and SDG 9 "Industry, innovation and infrastructures", in the subject Production Management, with the aim of achieving the competence "environmental awareness". From the perspective of the students, an evaluation of the educational experience is presented. The results show the success of the Flipped Classroom methodology in providing students with a holistic understanding of the principles of sustainable development and their application through the SDGs within their academic trajectory. In particular, this approach provides them with the skills and aptitudes to promote sustainability.

The article offers a comprehensive analysis of the historical development and future prospects for the food industry with a focus on management aspects. The study is based on the study of the stages of the evolution of this industry, including the periods of technological and socio-cultural changes that influenced its development. Historical analysis reveals the key decisive moments in the formation of the food industry, and also reveals the methods and approaches used for management decisions that have determined the industry's strategies over the years. The authors' research also draws attention to the impact of modern technologies and innovations on the food industry, as well as to changes in consumer preferences and environmental issues. Important aspects of production planning and management, which affect the competitiveness of enterprises in the industry, have been considered. In particular, the article highlights the need to adapt to changes in market conditions and consumer requirements, which becomes an important factor in the strategic planning of enterprises. The authors have also conducted the research on the perspective of the future development of the food industry, focusing on opportunities for innovation, sustainable development and global trends. In particular, the article discusses possible directions for the development of management strategies that can help enterprises adapt to future challenges and ensure their competitiveness. Therefore, this article reflects not only the historical aspects of the development of the food industry, but also provides the view of its future from the perspective of management, which makes it useful both for practitioners in the industry and for scholars interested in strategic management and innovation. [ABSTRACT FROM AUTHOR]

Amid advancements in information technology, this study explores the integration of blockchain technology in supply chain management, particularly for improving collaborative production mechanisms. Known for decentralization, transparency, and data security, blockchain is seen as a solution for issues like information delays and asymmetry in traditional supply chains. To address a gap in empirical research, a model incorporating blockchain for information collaboration in supply chain production management was developed using the Stackelberg game model. Furthermore, a consensus decision model aimed at enhancing supply chain collaboration was established within the blockchain network. These findings provide valuable insights into the practical benefits of blockchain in supply chain management, offering direction for future practice. [ABSTRACT FROM AUTHOR]

Copyright of GeSec: Revista de Gestao e Secretariado is the property of Sindicato das Secretarias e Secretarios do Estado de Sao Paulo (SINSESP) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper presents the results of a research work that aimed at investigating the usage of softbots – as digital intelligent software assistants – as a supporting technology to help in excelling smart production management composed of cyber-physical systems (CPS). This work also attempts to differentiate the many equivalent terms used in the literature to softbots, trying to demonstrate that all of them are just types of softbots. Softbots 4.0 acts as a smart humanmachine interface, representing a digital virtual assistant to handle human-related issues when implementing the concept of Operator 4.0. Yet, the concept of Softbot 4.0 is framed against the RAMI 4.0 model in a way to show how it can also be taken as an (intelligent) manufacturing entity. The main goal of Softbots 4.0 is to support the Operator 4.0 in interfacing with smart machines, robots, and systems, aiding people in the automatic, planned or pro-active execution of different, repetitive or complex tasks, efficiently in a more symbiotic human-machine environment. Five different cases have been selected for the assessment, implemented as software prototypes in different production management and shop floor control scenarios close to real CPS. The high potential of the softbots approach could be observed, especially when combined with other enabling technologies for Industry 4.0. A global assessment and reflections on these experiments are discussed at the end.

We develop a vision system for batch inspection by oven white paper model color by manufacturing a machine vision system for the oven manufacturing automation process. In the vision system, white paper object detection (spring), color clustering, and histogram extraction are performed. In addition, for the automated process of home appliances, we intend to develop an automatic mold combination detection algorithm that inspects the label position and direction (angle/coordinate) using deep learning.

This Community Service Program (PkM) aims to solve the difficulties faced by the Pusako Bundo coffee business in Kenagarian Pasie Laweh. The problems faced by partners are the production system that is still simple, the low production capacity so that producers have not met market needs. Efforts to improve product quality are carried out with assistance and training in production management. The activities carried out are in the form of increasing knowledge in the processing of coffee processing processes with the application of technology, so as to be able to prepare raw material needs and make production records, know product sanitation and innovation efforts. The implementation of the community service program has been able to provide good packaging, and provide knowledge to partners about good production systems to produce products with better quality and activity have a significant impact on the sustainability of the partner's business and have a significant impact on the sustainability of partners' businesses.

The proposed paper introduces an innovative approach based on the implementation of a multi-level Decision Support System (DSS) modelling processes in the industry. Specifically, the work discusses a theoretical Process Mining (PM) DSS model gaining digital knowledge by means of logics that are able to select the best decisions. The PM model is applied to an open dataset simulating a working scenario and defining a possible safety control method based on the risk assessment. The application of the PM model provides automatic alerting conditions based on a threshold of values detected by sensors. Specifically, the PM model is applied to worker security systems characterized by the environment with a risk of emission of smoke and gases. The PM model is improved by Artificial Intelligence (AI) algorithms by strengthening information through prediction results and improving the risk analysis. An Artificial Neural Network (ANN) MultilaLayer Perceptron (MLP) algorithm is adopted for the risk prediction by achieving the good computational performance of Mean Absolute Error (MAE) of 0.001. The PM model is first sketched by the Business Process Modelling and Notation (BPMN) method, and successively executed by means of the Konstanz Information Miner (KNIME) open source tool, implementing the process-controlling risks for different working locations. The goal of the paper is to apply the theoretical PM model by means of open source tools by enhancing how the multi-level approach is useful for defining a security procedure to control indoor worker environments. Furthermore, the article describes the key variables able to control production and worker safety for different industry sectors. The presented DSS PM model also can be applied to industry processes focused on production quality.

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Focusing on quantitative analysis and combining with qualitative analysis, this paper selects five benchmarking enterprises for quantitative evaluation of key production indicators, and completes the transverse and overall comparison of data at all levels of production management. It also carries out qualitative analysis by positioning research for Enterprise B, and points out directions of production management optimization. With benchmarking and targeted diagnosis and optimization, production and operation management level of the enterprise can be improved.

En este artículo se trabaja el concepto transorganización de Eikhof (2014) y se propone como forma para describir a las micro-organizaciones creativas, que se plantea son bastante significativas en el campo de las industrias creativas. A partir de esta contextualización teórica, se busca proponer la auto-gestión como la estrategia principal que utilizan estas organizaciones para enfrentarse a su contexto ambiguo e incierto y así poder utilizar la improvisación (Hatch, 1990) desde el flojo acoplamiento de funciones (Douglas y Weick, 1990) como estructuración. Para eso el trabajo propone los acercamientos teóricos que ha tenido la academia frente al emprendimiento creativo y así centrarse en estos conceptos teóricos; posteriormente analiza el efecto de dichos conceptos desde la economía; presenta la herramienta metodológica utilizada desde un enfoque cualitativo del estudio de caso con observación participante y entrevistas a profundidad; finalmente hace un estudio de tres casos de micro-organizaciones creativas en la música para darle cabida empírica a la propuesta teórica inicial.