A national survey data for the technical and economic assessment of African catfish production in Nigeria before and during the COVID-19 period.

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.

[Application progress on data-driven technologies in intelligent manufacturing of traditional Chinese medicine extraction].

The application of new-generation information technologies such as big data, the internet of things(IoT), and cloud computing in the traditional Chinese medicine(TCM)manufacturing industry is gradually deepening, driving the intelligent transformation and upgrading of the TCM industry. At the current stage, there are challenges in understanding the extraction process and its mechanisms in TCM. Online detection technology faces difficulties in making breakthroughs, and data throughout the entire production process is scattered, lacking valuable mining and utilization, which significantly hinders the intelligent upgrading of the TCM industry. Applying data-driven technologies in the process of TCM extraction can enhance the understanding of the extraction process, achieve precise control, and effectively improve the quality of TCM products. This article analyzed the technological bottlenecks in the production process of TCM extraction, summarized commonly used data-driven algorithms in the research and production control of extraction processes, and reviewed the progress in the application of data-driven technologies in the following five aspects: mechanism analysis of the extraction process, process development and optimization, online detection, process control, and production management. This article is expected to provide references for optimizing the extraction process and intelligent production of TCM.

Integrating sustainability into production scheduling in hybrid flow-shop environments.

Global energy consumption is projected to grow by nearly 50% as of 2018, reaching a peak of 910.7 quadrillion BTU in 2050. The industrial sector accounts for the largest share of the energy consumed, making energy awareness on the shop floors imperative for promoting industrial sustainable development. Considering a growing awareness of the importance of sustainability, production planning and control require the incorporation of time-of-use electricity pricing models into scheduling problems for well-informed energy-saving decisions. Besides, modern manufacturing emphasizes the role of human factors in production processes. This study proposes a new approach for optimizing the hybrid flow-shop scheduling problems (HFSP) considering time-of-use electricity pricing, workers' flexibility, and sequence-dependent setup time (SDST). Novelties of this study are twofold: to extend a new mathematical formulation and to develop an improved multi-objective optimization algorithm. Extensive numerical experiments are conducted to evaluate the performance of the developed solution method, the adjusted multi-objective genetic algorithm (AMOGA), comparing it with the state-of-the-art, i.e., strength Pareto evolutionary algorithm (SPEA2), and Pareto envelop-based selection algorithm (PESA2). It is shown that AMOGA performs better than the benchmarks considering the mean ideal distance, inverted generational distance, diversification, and quality metrics, providing more versatile and better solutions for production and energy efficiency.

Process Parameter Prediction for Fused Deposition Modeling Using Invertible Neural Networks.

Additive manufacturing has revolutionized prototyping and small-scale production in the past years. By creating parts layer by layer, a tool-less production technology is established, which allows for rapid adaption of the manufacturing process and customization of the product. However, the geometric freedom of the technologies comes with a large number of process parameters, especially in Fused Deposition Modeling (FDM), all of which influence the resulting part's properties. Since those parameters show interdependencies and non-linearities, choosing a suitable set to create the desired part properties is not trivial. This study demonstrates the use of Invertible Neural Networks (INN) for generating process parameters objectively. By specifying the desired part in the categories of mechanical properties, optical properties and manufacturing time, the demonstrated INN generates process parameters capable of closely replicating the desired part. Validation trials prove the precision of the solution with measured properties achieving the desired properties to up to 99.96% and a mean accuracy of 85.34%.

Control of odor emissions from livestock farms: A review.

Odor emission seriously affects human and animal health, and the ecological environment. Nevertheless, a systematic summary regarding the control technology for odor emissions in livestock breeding is currently lacking. This paper summarizes odor control technology, highlighting its applicability, advantages, and limitations, which can be used to evaluate and identify the most appropriate methods in livestock production management. Odor control technologies are divided into four categories: dietary manipulation (low-crude protein diet and enzyme additives in feed), in-housing management (separation of urine from feces, adsorbents used as litter additive, and indoor environment/manure surface spraying agent), manure management (semi-permeable membrane-covered, reactor composting, slurry cover, and slurry acidification), and end-of-pipe measures for air treatment (wet scrubbing of the exhaust air from animal houses and biofiltration of the exhaust air from animal houses or composting). Findings of this paper provide a theoretical basis for the application of odor control technology in livestock farms.

Science-based quality control in boar semen production.

The ever-increasing understanding of sperm physiology, combined with innovative technical advances, continuously furthers the development of boar semen production management. These improvements pave the way for the future implementation of modified quality assurance concepts. This review provides an overview of current trends and new approaches in boar semen production, focusing on: the improvement of hygienic standards, alternatives to the use of antibiotics including the application of cold temperature storage and the utilization of antimicrobial additives, as well as the implementation of new quality control tools. Furthermore, the influence of dilution and temperature management, as well as new possibilities for an improvement of boar semen shipping and storage conditions are reviewed.

Application progress on data-driven technologies in intelligent manufacturing of traditional Chinese medicine extraction / 中国中药杂志

The application of new-generation information technologies such as big data, the internet of things(IoT), and cloud computing in the traditional Chinese medicine(TCM)manufacturing industry is gradually deepening, driving the intelligent transformation and upgrading of the TCM industry. At the current stage, there are challenges in understanding the extraction process and its mechanisms in TCM. Online detection technology faces difficulties in making breakthroughs, and data throughout the entire production process is scattered, lacking valuable mining and utilization, which significantly hinders the intelligent upgrading of the TCM industry. Applying data-driven technologies in the process of TCM extraction can enhance the understanding of the extraction process, achieve precise control, and effectively improve the quality of TCM products. This article analyzed the technological bottlenecks in the production process of TCM extraction, summarized commonly used data-driven algorithms in the research and production control of extraction processes, and reviewed the progress in the application of data-driven technologies in the following five aspects: mechanism analysis of the extraction process, process development and optimization, online detection, process control, and production management. This article is expected to provide references for optimizing the extraction process and intelligent production of TCM.

Analysis of Lean Six Sigma Use in Pharmaceutical Production

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.

Interspecific variation in wildlife responses to cattle, swine and chicken feed in the forests surrounding poultry farms.

To strengthen farm biosecurity, wildlife behaviors around livestock environments require significant attention. Livestock feed is considered one of essential factors that attract wildlife to the livestock environment. We experimentally studied wildlife response to cattle, swine, and chicken concentrated feeds in the forests surrounding poultry farms. In 14 feeding sites, four feed conditions were established: without feed (control); cattle feed; chicken feed; and swine feed. Wildlife behaviors at each feed point were monitored using infrared cameras. In 3,175 videos, 10 mammals were photographed on 10 or more occasions. Wildlife more frequently appeared at the points with feed than without feed. In addition, the number of videos that captured foraging or interest behaviors was largest for swine feed, followed by chicken feed, then cattle feed. There was a large difference among wildlife in their response to livestock feeds, although each species did not have a strong preference for a specific feed. Livestock feeds invite frequent visits by high and moderate response groups, especially omnivores and carnivores with omnivorous tendencies. Therefore, to protect against such wildlife intrusion, leftover feed and feed storage must be properly managed. This study also suggests that livestock feeds may not cause intrusions by rare response group species; hence, if their intrusions occur, they may be due to factors other than livestock feed. The study situation can partly reflect actual feed-stealing situations. The results will contribute to consider the properly management to protect livestock environments from wildlife intrusions.

Trust in artificial intelligence within production management - an exploration of antecedents.

Industry 4.0, big data, predictive analytics, and robotics are leading to a paradigm shift on the shop floor of industrial production. However, complex, cognitive tasks are also subject of change, due to the development of artificial intelligence (AI). Smart assistants are finding their way into the world of knowledge work and require cooperation with humans. Here, trust is an essential factor that determines the success of human-AI cooperation. Within this article, an analysis within production management identifies possible antecedent variables on trust in AI and evaluates these due to interaction scenarios with AI. The results of this research are five antecedents for human trust in AI within production management. From these results, preliminary design guidelines are derived for a socially sustainable human-AI interaction in future production management systems. Practitioner summary: In the future, artificial intelligence will assist cognitive tasks in production management. In order to make good decisions, humans trust in AI has to be well calibrated. For trustful human-AI interactions, it is beneficial that humans subjectively perceive AI as capable and comprehensible and that they themselves are digitally competent.

Taguchi based Case study in the automotive industry: nonconformity decreasing with use of Six Sigma methodology.

In this study, we applied a conceptual Six Sigma/design of experiment hybrid framework that aims to integrate the Taguchi method and Six Sigma for process improvement in a complex industrial environment. In this context, the Six Sigma methodology was employed on a company operating within the automotive industry to improve a manufacturing process which caused a customer complaint within the company. Studies employing the Taguchi experiment design usually focus on a single variable and neglect the effects of adjustments on remaining quality characteristics. In this study, a multi-response Taguchi design of experiment was preferred, and all of the quality characteristics were taken into account. In our study, define, measure, analysis, improve and control phases were used to reduce the nonconformity rate from 23.940 percent (baseline) to 0.049 percent. As a result of implementing Six Sigma, the sigma level increased from 2.21 (baseline) to 4.80.

[Finding Analysis of Medical Device Manufacturer Audit in Suzhou Industrial Park for the Last Three Years].

OBJECTIVE: Common findings are to be found from 144 different type of medical device manufacturers' audit reports which are from Jan. 2017 to Jun. 2019. Advise is to be provided for medical device manufacturers on continual improvement. METHODS: Classify and analyze the on-site audit findings from different type of medical device manufacturers. RESULTS: The frequency of findings from chapter production management, buildings and facilities, quality control are comparatively high. CONCLUSIONS: The key to improve the quality management system is to cultivate the staff sense of continual improvement of quality system, improve the staff ability of finding and solving problems, encourage staff participation in quality system, fit the quality system on product realization.

Finding Analysis of Medical Device Manufacturer Audit in Suzhou Industrial Park for the Last Three Years / 中国医疗器械杂志

OBJECTIVE@#Common findings are to be found from 144 different type of medical device manufacturers' audit reports which are from Jan. 2017 to Jun. 2019. Advise is to be provided for medical device manufacturers on continual improvement.@*METHODS@#Classify and analyze the on-site audit findings from different type of medical device manufacturers.@*RESULTS@#The frequency of findings from chapter production management, buildings and facilities, quality control are comparatively high.@*CONCLUSIONS@#The key to improve the quality management system is to cultivate the staff sense of continual improvement of quality system, improve the staff ability of finding and solving problems, encourage staff participation in quality system, fit the quality system on product realization.

New trends in production management in European pig AI centers.

Reducing the number of spermatozoa per artificial insemination (AI) dose and managing semen in ways to ensure greater quality at the same time represents current challenges with sperm processing in pig AI centers. Based on a multi-year comparative analysis of process steps in different pig AI centers, and complementary experimental studies under standardized laboratory conditions, current process standards for the preservation of boar semen have been updated and new ones developed. Currently, these standards represent an integral part of the quality assurance of 29 European pig AI centers in ten different organizations in Germany, Switzerland and Austria. Improvement of hygiene management and guidelines for prudent use of antibiotics have become key issues. Furthermore, new quality control tools have been implemented in the processing and transport of boar semen: e.g. refractometry as an easy-to-use tool to estimate extender osmolarity and 'mobile sensing' apps for continuous monitoring of various environmental parameters. Moreover, based on a series of experiments under laboratory and field conditions, guidelines for optimizing the dilution process, and time and temperature management during boar semen processing, have been developed and implemented. Similarly, recommendations for the handling of semen doses during storage have been renewed. Over the years, the efficiency of the quality assurance system has been reflected by a decrease of bacterial contamination and a concomitant increase in the quality of semen doses. In conclusion, science-based quality assurance is an effective way to improve the production performance in pig AI centers, resulting in high quality and economically-priced semen for pig producers. Increasing knowledge of sperm physiology together with computational and technical innovations will continue to develop and modify quality assurance concepts in the future.

Decisiones estratégicas de operaciones en la producción sostenible: análisis de tendencias en investigación / Strategic operations decisions on sustainable production: analysis of research trends / Decisões de operações estratégicas em produção sustentável: análise de tendências em pesquisa

Resumen Los cambios en normatividad y acceso a recursos naturales permiten repensar el proceso de toma de decisiones sobre métodos de producción sostenibles, sin alterar estabilidad y posición competitiva en las organizaciones. Como metodología se realizó un estudio bibliométrico para 576 documentos recuperados de la base de datos Scopus, a fin de comprender tendencias en investigación. A partir de Ley de Lotka y Ley de Pareto se desarrollaron indicadores de calidad, cantidad y estructura. Los resultados exhiben como tendencias de investigación futura: Life Cycle Assessment, plantas de producción sostenibles, análisis de riesgo en producción, green manufacturing y gestión sostenible en proveedores.

Abstract Changes in regulations and access to natural resources allow us to rethink the decision-making process regarding sustainable production methods without altering the stability and competitive advantage of organizations. As methodology, a bibliometric study was carried out for 576 documents retrieved from the Scopus database in order to understand trends in research. Lotka Law and Pareto Law were used to build quality, quantity and structure indicators. The results show as future research the following trends: Life Cycle Assessment, sustainable production plants, risk analysis in production, green manufacturing and sustainable management in suppliers.

Resumo As mudanças na normatividade e acesso aos recursos naturais permitem repensar o processo de toma de decisões sob métodos de produção sustentáveis, sem alterar a estabilidade e vantagem competitiva nas organizações. Como metodologia realizouse um estudo bibliométrico para 576 documentos recuperados da base de dados Scopus, com o fim de compreender tendências na pesquisa. A partir da Lei do Lotka e a Lei do Pareto desenvolveram-se indicadores de qualidade, quantidade e estrutura. Os resultados amostram como tendências da futura pesquisa: Life Cycle Assessment, usinas de produção sustentáveis, análises de risco em produção, green manufacturing e gestão sustentável em fornecedores.

Chimeric antigen receptor-T cell therapy manufacturing: modelling the effect of offshore production on aggregate cost of goods.

Cell and gene therapies have demonstrated excellent clinical results across a range of indications with chimeric antigen receptor (CAR)-T cell therapies among the first to reach market. Although these therapies are currently manufactured using patient-derived cells, therapies using healthy donor cells are in development, potentially offering avenues toward process improvement and patient access. An allogeneic model could significantly reduce aggregate cost of goods (COGs), potentially improving market penetration of these life-saving treatments. Furthermore, the shift toward offshore production may help reduce manufacturing costs. In this article, we examine production costs of an allogeneic CAR-T cell process and the potential differential manufacturing costs between regions. Two offshore locations are compared with regions within the United States. The critical findings of this article identify the COGs challenges facing manufacturing of allogeneic CAR-T immunotherapies, how these may evolve as production is sent offshore and the wider implication this trend could have.

Design and Simulation of Production and Maintenance Management Applying the Viable System Model: The Case of an OEM Plant.

Designing, changing and adapting organizations to secure viability is challenging for manufacturing companies. Researchers often fail to holistically design or transform production systems. Reasons are often the conflict of interests between production and maintenance, the temporal divergence of their activities and their organizational structure. Thus, the aim of this study is to propose a holistic approach of how production and maintenance can be designed, changed or managed. Hereby, the Viable System Model was applied. This structure can be applied to any kind of structured organization and for its management with goals to be achieved in modern society; however, focus of the research is the coordination of production and maintenance management. The goal of the developed model is to be able to react to some potential production environments by taking coordinated decisions correctly and in the right moment based on the needed information. To ensure this, standardized communication channels were defined. In conclusion, this proposed approach enables production systems to have internal mechanisms to secure viability depending on all potential environment scenarios.

Biochar reduces nitrate level in red beet.

Impacts of red beet consumption both on human and animal health are subject of intense research. In particular, products that are not heat-processed contain plethora of bioactive compounds that hold promise against numerous degenerative and aging-associated diseases. However, high level of nitrates (typically more than 2 g NO3- kg-1) whose health effects are perceived with reasoned objections counterbalance these benefits. Following the above, from a certain level, the increased consumption of red beet has contrary impacts, creating a limiting factor not only from the economic point of view but also in terms of beneficial compounds intake. Reduction of NO3- levels (- 35%) has been achieved by soil amendment via increased doses of biochar. The data obtained indicates that the mechanism can be explained as follows. The soil improvement reduces soil density, increases soil temperature, improves water retention, and other prerequisites for increased activity of soil microorganisms. Accelerated metabolism of soil biota turned more nitrogen from fertilizers into organic forms. Hence, less mineral nitrogen is left for red beet intake.

Customized recommendations for production management clusters of North American automatic milking systems.

Automatic milking systems (AMS) are implemented in a variety of situations and environments. Consequently, there is a need to characterize individual farming practices and regional challenges to streamline management advice and objectives for producers. Benchmarking is often used in the dairy industry to compare farms by computing percentile ranks of the production values of groups of farms. Grouping for conventional benchmarking is commonly limited to the use of a few factors such as farms' geographic region or breed of cattle. We hypothesized that herds' production data and management information could be clustered in a meaningful way using cluster analysis and that this clustering approach would yield better peer groups of farms than benchmarking methods based on criteria such as country, region, breed, or breed and region. By applying mixed latent-class model-based cluster analysis to 529 North American AMS dairy farms with respect to 18 significant risk factors, 6 clusters were identified. Each cluster (i.e., peer group) represented unique management styles, challenges, and production patterns. When compared with peer groups based on criteria similar to the conventional benchmarking standards, the 6 clusters better predicted milk produced (kilograms) per robot per day. Each cluster represented a unique management and production pattern that requires specialized advice. For example, cluster 1 farms were those that recently installed AMS robots, whereas cluster 3 farms (the most northern farms) fed high amounts of concentrates through the robot to compensate for low-energy feed in the bunk. In addition to general recommendations for farms within a cluster, individual farms can generate their own specific goals by comparing themselves to farms within their cluster. This is very comparable to benchmarking but adds the specific characteristics of the peer group, resulting in better farm management advice. The improvement that cluster analysis allows for is characterized by the multivariable approach and the fact that comparisons between production units can be accomplished within a cluster and between clusters as a choice.

Wicked problems: a value chain approach from Vietnam's dairy product.

ABSTRACT: In the past few years, dairy industry has become one of the fastest growing sectors in the packaged food industry of Vietnam. However, the value-added creation among different activities in the value chain of Vietnam dairy sector is distributed unequally. In the production activities, the dairy farmers gain low value-added rate due to high input cost. Whereas the processing activities, which managed by big companies, generates high profitability and Vietnamese consumers seem to have few choices due to the lack of dairy companies in the market. These wicked problems caused an unsustainable development to the dairy value chain of Vietnam. This paper, therefore, will map and analyze the value chain of the dairy industry in Vietnam. It will also assess the value created in each activity in order to imply solutions for a sustainable development of Vietnam's dairy industry. JEL CODES: M10, M11.