Considering the importance of increasingly rapid industrial development, business people must be aware of the orientation towards product quality. The manufacturing industry has an important role in industrial development. It is hoped that it will be able to grow and have advantages in industrial development, therefore it is necessary to improve and increase product quality. The company continues to strive to maintain and improve product quality and increase productivity so that customers are satisfied with the products produced. One way that needs to be done is to reduce the number of defective products in the production process. This effort is one way of continuous improvement carried out by PT. ABC and companies operating in the same field. The ceramic wall production process has relatively high demand but still has a high level of defects. Based on information on production data and data on the number of defects for the period January – September 2023, wall ceramic production has a defect rate of 3.86%. Companies must reduce the number of defects to achieve company targets. This research aims to improve the production process of wall ceramics by minimizing the number of defective products. This research uses the six sigma method with the DMAIC (Define, Measure, Analyze, Improve, Control) tool assisted by the FMEA (Failure Mode and Analysis) method. Corrective action to reduce defects based on the 5 Why analysis is to find out what the problem is and ask "why" and "what is the root of the problem". The research results show that there are 4 types of defects which have a large number of defects, namely Rupture Defects, Application Defects, Peeling Defects and Hole Defects. From the research results, solutions were obtained for the emergence of several types of defects in the wall ceramic production process, namely by providing planning suggestions and corrective actions which are discussed this time. At the defect calculation stage, Broken produces a DPMO value of 29.362 with a sigma level of 3.39 with a sigma level of 3.48, Defect Peeled produces a DPMO value of 28.044 with a sigma level of 3.38, and holes are defective. resulting in a DPMO value of 26,020 with a sigma value of 3.45 from the data calculation results, it is still not enough to meet the company's target at the sigma level, therefore the company must make quality improvements to achieve the main target at the sigma level.
Purpose The service sector is at an inflection point with regard to productivity gains and service industrialization similar to the industrial revolution in manufacturing that started in the eighteenth century. Robotics in combination with rapidly improving technologies like artificial intelligence (AI), mobile, cloud, big data and biometrics will bring opportunities for a wide range of innovations that have the potential to dramatically change service industries. The purpose of this paper is to explore the potential role service robots will play in the future and to advance a research agenda for service researchers. Design/methodology/approach This paper uses a conceptual approach that is rooted in the service, robotics and AI literature. Findings The contribution of this paper is threefold. First, it provides a definition of service robots, describes their key attributes, contrasts their features and capabilities with those of frontline employees, and provides an understanding for which types of service tasks robots will dominate and where humans will dominate. Second, this paper examines consumer perceptions, beliefs and behaviors as related to service robots, and advances the service robot acceptance model. Third, it provides an overview of the ethical questions surrounding robot-delivered services at the individual, market and societal level. Practical implications This paper helps service organizations and their management, service robot innovators, programmers and developers, and policymakers better understand the implications of a ubiquitous deployment of service robots. Originality/value This is the first conceptual paper that systematically examines key dimensions of robot-delivered frontline service and explores how these will differ in the future.
Abstract Digitization and intelligentization of manufacturing process is the need for today’s industry. The manufacturing industries are currently changing from mass production to customized production. The rapid advancements in manufacturing technologies and applications in the industries help in increasing productivity. The term Industry 4.0 stands for the fourth industrial revolution which is defined as a new level of organization and control over the entire value chain of the life cycle of products; it is geared towards increasingly individualized customer requirements. Industry 4.0 is still visionary but a realistic concept which includes Internet of Things, Industrial Internet, Smart Manufacturing and Cloud based Manufacturing. Industry 4.0 concerns the strict integration of human in the manufacturing process so as to have continuous improvement and focus on value adding activities and avoiding wastes. The objective of this paper is to provide an overview of Industry 4.0 and understanding of the nine pillars of Industry 4.0 with its applications and identifying the challenges and issues occurring with implementation the Industry 4.0 and to study the new trends and streams related to Industry 4.0.
Abstract We analyze for the first time the economic contributions of modern industrial robots, which are flexible, versatile, and autonomous machines. We use novel panel data on robot adoption within industries in seventeen countries from 1993 to 2007 and new instrumental variables that rely on robots’ comparative advantage in specific tasks. Our findings suggest that increased robot use contributed approximately 0.36 percentage points to annual labor productivity growth, while at the same time raising total factor productivity and lowering output prices. Our estimates also suggest that robots did not significantly reduce total employment, although they did reduce low-skilled workers’ employment share.
Abstract Improving agricultural carbon productivity is crucial for advancing economic and social green and low-carbon development, with the digital development initiative exemplified by the digital village construction pilot policy being instrumental in enhancing agricultural “quality and efficiency.” This study treats the pilot policy for digital rural development as a quasi-natural experiment of external shock policy, employing the difference-in-differences (DID) method to dynamically assess its impact mechanisms and pathways on agricultural carbon productivity using panel data from 620 counties (cities and districts) in major grain-producing regions from 2018 to 2022. The findings reveal that the implementation of the digital rural development pilot policy effectively promotes a significant increase in local agricultural carbon productivity, with adjacent regions experiencing similar effects. Among these, inland regions exhibit weaker policy effects compared to coastal regions, and the policy relationships in urban–rural integrated development zones and east-central-west collaborative development zones also follow this pattern. Similarly, the policy effects of large-scale operations are superior to those of small-scale operations. The policy further highlights the two key mechanisms—industrial agglomeration and service integration—underlying its impact on China’s agricultural carbon productivity. Additionally, the increase in agricultural entrepreneurship activity exhibits a trend of increasing marginal benefits in relation to policy implementation.
Nutrition. Foods and food supply, Agricultural industries
Breaking through the constraints of traditional agricultural resources and expanding food supply channels have become essential for safeguarding food security. The non-timber forest-based economy (NTFE), which integrates multiple understory production activities including planting, breeding, and foraging, expands the variety of food sources and provides a new pathway for enhancing regional diversified food supply capacity (DFSC). Based on this perspective, this study constructs evaluation indicator systems for both DFSC and NTFE development. The entropy-weighted TOPSIS method is employed to measure the levels of DFSC and NTFE development across 31 Chinese provinces from 2011 to 2022. A two-way fixed effects model and a spatial Durbin model are applied to empirically investigate the mechanisms through which the NTFE enhances DFSC. The results show the following: (1) Between 2011 and 2022, both the DFSC and the level of NTFE development in China exhibited a sustained upward trend. Specifically, the level of NTFE development grew rapidly before 2019, with a slowdown in growth in the later years, while DFSC maintained a steady increase throughout the study period. (2) NTFE development significantly promotes DFSC. (3) The NTFE enhances DFSC by facilitating the upgrading of the forestry industrial structure and improving forestland productivity. (4) The NTFE generates positive spatial spillover effects on DFSC, and these spillover effects are stronger than direct local effects.
Continuous cropping poses a severe threat to the sustainability of industrial crops like flue-cured tobacco (Nicotiana tabacum L.) by degrading the rhizosphere micro-ecosystem. Organic amendments offer a promising remediation strategy, yet the systemic mechanisms linking amendment-induced changes in the rhizosphere environment to plant performance remain poorly quantified. Using a multi-omics approach—integrating rhizosphere soil microbial profiling (16S rRNA and ITS sequencing) with root exudate metabolomics (UHPLC-MS/MS)—this study investigated how four organic amendments (corn straw, cattle manure, rapeseed cake, and humic acid fertilizer) alleviate this obstacle in a continuous flue-cured tobacco system. Cattle manure and humic acid fertilizer were most effective in promoting plant growth, increasing plant height by 6.78% and 7.31%, and root dry weight by 55.51% and 71.26%, respectively, compared to the non-amended control. These amendments consistently elevated rhizosphere pH and organic matter, while reducing nutrient availability. The re-engineered soil environment was associated with a marked reduction in autotoxic phenolic acids (e.g., benzoic and cinnamic acid) and suppression of pathogenic fungi such as Fusarium and Plectosphaerella. Partial least squares path modeling (PLS-PM) integrated these disparate observations, verifying that the improvements in plant growth were primarily mediated through the rhizosphere soil property-driven suppression of autotoxins and pathogenic fungi, rather than through direct effects. These findings provide a mechanistic framework for selectively deploying organic amendments to manage rhizosphere health, offering a sustainable strategy to enhance productivity and break the cycle of soil sickness in continuous cropping systems for tobacco and other susceptible industrial crops.
A. V. Chashynski, V. A. Kozlov, D. V. Bashko
et al.
Enhancing the efficiency of potato farming requires continuous development of new highly productive cultivars with a set of valuable agronomic traits. Such work is impossible without a sufficient stock of new, genetically diverse source material for potato breeding. Therefore, expanding, studying, and preserving potato genetic resources collections in the Republic of Belarus is an important task to provide the domestic potato breeding practice with new sources of valuable traits. The objective of this research was to examine interspecific potato hybrids developed at the Potato Genetic Resources Department of the N.I. Vavilov All-Russian Institute of Plant Genetic Resources (VIR) for their key agronomic characters (productivity; resistance to viruses, late blight, and blackleg; starch content; suitability for industrial processing into potato products, etc.) through breeding-oriented assessment and marker analysis searching for effective alleles of genes associated with carbohydrate synthesis.The research identified sources of resistance to the oomycete Phytophthora infestans (Mont.) de Bary, blackleg pathogens, and viruses, as well as sources of high productivity and suitability for industrial processing into potato products after five months of cold storage without reconditioning. The PCR analysis helped to identify hybrids carrying the markers Stp23-8b, InvGF-4d, and InvGF-4b – effective alleles of genes responsible for carbohydrate synthesis in tubers. The identified hybrids are recommended as sources of valuable agronomic traits for potato breeding practice.
Abstract Background Ducks are globally important poultry species and a major source of farm animal products, including meat, eggs, and feathers. A thorough understanding of the functional genomic and transcriptomic sequences is crucial for improving production efficiency. Result This study constructed the largest duck mRNA expression atlas among all waterfowl species to date. The atlas encompasses 1,257 tissue samples across 30 tissue types, representing all major organ systems. Using advanced clustering analysis, we established co-expression network clusters to describe the transcriptional features in the duck mRNA expression atlas and, when feasible, assign these features to unique tissue types or pathways. Additionally, we identified 27 low-variance, highly expressed housekeeping genes suitable for gene expression experiments. Furthermore, in-depth analysis revealed potential sex-biased gene expression patterns within tissues and specific gene expression profiles in meat-type and egg-type ducks, providing valuable resources to understand the genetic basis of sex differences and particular phenotypes. This research elucidates the biological processes affecting duck productivity. Conclusion This study presents the most extensive gene expression atlas for any waterfowl species to date. These findings are of significant value for advancing duck biological research and industrial applications.
Yasmine El Belghiti, Abdelfattah Mouloud, Samir Tetouani
et al.
The main thrust of the study is the need to cut down the time taken for mold changes in plastic injection molding which is fundamental to the productivity and efficiency of the process. The research encompasses Lean Manufacturing, DMAIC, and SMED which are improved using fuzzy logic and AI for rapid changeover optimization on the NEGRI BOSSI 650 machine. A decrease in downtime by 65% and an improvement in the Process Cycle Efficiency by 46.8% followed the identification of bottlenecks, externalizing tasks, and streamlining workflows. AI-driven analysis could make on-the-fly adjustments, which would ensure that resources are better allocated, and thus sustainable performance is maintained. The findings highlight how integrating Lean methods with advanced technologies enhances operational agility and competitiveness, offering a scalable model for continuous improvement in industrial settings.
This article compares the socio-economic development of the two industrial EU regions, the Silesian Voivodeship Poland and the Düsseldorf District in North Rhine–Westphalia, Germany, in the last 20 years of the 21st century. The Ninth Cohesion Report, the EU Regional Competitiveness Index 2.0, and the two concepts of the regional development trap and just transition in the EU were used. It investigated whether the applied EU regional policy, cohesion policy, had the expected effect of strengthening sustainable growth in the regions. This article aims to compare development trajectories, identify development traps and barriers, consider the just transition in the analyzed regions, and provide recommendations for regional policy. Those heavily industrialized regions must respond to the demographic challenges of labor shortages and an aging population. In the case of the Silesia region, the indicated course of action includes labor activation of women and migration management. For both regions, improving productivity is the key. The vital economic challenges include: for the Silesian Voivodeship—strengthening innovation; for the Düsseldorf region—maintaining innovation momentum and increasing resilience. Developing skills that meet industries’ needs is essential. Regarding social cohesion, the Silesia region should focus on equality measures. On the other hand, the Düsseldorf region should strengthen social protection against poverty.
National enterprises are facing a very important task of increasing labour productivity as they need resources to operate in the conditions of personnel shortage and mobilization economy. Some of them have already accumulated certain experience of implementation of various management and technology innovations that allow to increase business efficiency; others use acceleration programs based on the lean technology implementation and provided by the state within the framework of the national project “Labour Productivity”. This makes it relevant to understand the previously accumulated experience in using lean manufacturing in the modern context. The purpose of the work is to study the experience of a number of industrial enterprises (RUSAL, NAPO, Elsib, SIBECO) on implementing the projects devoted to increasing labour productivity using lean technology, to summarize their implementation and make recommendations on how to apply them in national business. Methods of study involve analysis of the national manufacturing companies’ experience, interviews with experts, analysis of documents on the projects on increasing organization efficiency. The results of the study conducted allowed making the conclusion that implementation of lean technologies requires their adaptation to sectoral, regional, corporate specificity and further development to meet the demands business and state are facing. Analysis of the above mentioned companies’ experience has shown that despite the obvious effectiveness of using lean manufacturing to involve the employees into the system of constant improvements they fail to ensure proper direct growth of labour productivity. The recommendations can be used in the practice of the companies that are starting to implement lean technologies.
In many countries, declining demand in energy-intensive industries such as cement, steel, and aluminum is leading to industrial overcapacity. Although industrial overcapacity is traditionally envisioned as problematic and resource-wasteful, it could unlock energy-intensive industries' flexibility in electricity use. Here, using China's aluminum smelting industry as a case study, we evaluate the system-level cost-benefit of retaining energy-intensive industries overcapacity for flexible electricity use in decarbonized energy systems. We find that overcapacity can enable aluminum smelters to adopt a seasonal operation paradigm, ceasing production during winter load peaks that are exacerbated by heating electrification and renewable seasonality. This seasonal operation paradigm could reduce the investment and operational costs of China's decarbonized electricity system by 23-32 billion CNY/year (11-15% of the aluminum smelting industry's product value), sufficient to offset the increased smelter maintenance and product storage costs associated with overcapacity. It may also provide an opportunity for seasonally complementary labor deployment across the aluminum smelting and thermal power generation sectors, offering a potential pathway for mitigating socio-economic disruptions caused by industrial restructuring and energy decarbonization.
The construction industry is presently going through a transformation led by adopting digital technologies that leverage Artificial Intelligence (AI). These industrial AI solutions assist in various phases of the construction process, including planning, design, production and management. In particular, the production phase offers unique potential for the integration of such AI-based solutions. These AI-based solutions assist site managers, project engineers, coordinators and other key roles in making final decisions. To facilitate the decision-making process in the production phase of construction through a human-centric AI-based solution, it is important to understand the needs and challenges faced by the end users who interact with these AI-based solutions to enhance the effectiveness and usability of these systems. Without this understanding, the potential usage of these AI-based solutions may be limited. Hence, the purpose of this research study is to explore, identify and describe the key factors crucial for developing AI solutions in the construction industry. This study further identifies the correlation between these key factors. This was done by developing a demonstrator and collecting quantifiable feedback through a questionnaire targeting the end users, such as site managers and construction professionals. This research study will offer insights into developing and improving these industrial AI solutions, focusing on Human-System Interaction aspects to enhance decision support, usability, and overall AI solution adoption.
The rise of Generative AI (GAI) and Large Language Models (LLMs) has transformed industrial landscapes, offering unprecedented opportunities for efficiency and innovation while raising critical ethical, regulatory, and operational challenges. This study conducts a text-based analysis of 160 guidelines and policy statements across fourteen industrial sectors, utilizing systematic methods and text-mining techniques to evaluate the governance of these technologies. By examining global directives, industry practices, and sector-specific policies, the paper highlights the complexities of balancing innovation with ethical accountability and equitable access. The findings provide actionable insights and recommendations for fostering responsible, transparent, and safe integration of GAI and LLMs in diverse industry contexts.