Large Manufacturing Plant Research Articles

MASHYNOBUDIVNYKY SETTLEMENT IN KHARKIV: STAGES OF DEVELOPMENT AND CONTEMPORARY CHALLENGES

This article examines the development stages and current challenges faced by the Mashynobudivnykiv workers’ settlement in Kharkiv, Ukraine. Initially formed during the Soviet industrialization era, this settlement was built around large manufacturing plants and factories, serving as housing for the workers of these industrial enterprises. Over the decades, the settlement has witnessed significant architectural, social, and infrastructural transformations, but it now faces a critical point due to the decline of its industrial base and aging housing stock. The settlement’s original purpose has largely diminished, leading to a range of socio-economic issues, including unemployment, deteriorating living conditions, and inadequate infrastructure. The article focuses on the architectural heritage of the settlement, analyzing its historical significance as an example of Soviet industrial housing development. The research outlines the specific challenges related to the modernization of the settlement’s infrastructure, particularly the need to balance preserving its architectural character with the demands of modern urban living. Attention is given to issues of energy inefficiency, lack of green spaces, and the broader socio-economic decline impacting the area. In addition to a historical audit of the settlement, the article explores urban planning strategies that could help revitalize Mashynobudivnykiv settlement. The author discusses potential avenues for redevelopment, including renovation of existing buildings, introducing new functional uses for outdated industrial areas, and improving local infrastructure to enhance the quality of life for residents. The integration of modern sustainable development practices, such as energy-efficient housing and green urban planning, is considered critical to the settlement’s long-term viability within the larger context of Kharkiv’s urban growth. The article concludes by proposing comprehensive renovation and revitalization strategies that could rejuvenate the Mashynobudivnykiv settlement while maintaining its historical value. The proposed urban interventions focus on improving living conditions, promoting social cohesion, and fostering economic opportunities, which are essential for the sustainable development of this historic workers’ district. Through these efforts, the Mashynobudivnykiv settlement could serve as a model for the successful transformation of similar post-industrial urban areas in Ukraine. Keywords: Soviet industrialization, architectural heritage, renovation, revitalization, sustainable urbanism.

The rapid construction method of the digital twin polymorphic model for discrete manufacturing workshop

The modeling process is resource-intensive, time-consuming, and expensive due to the large number and variety of production and auxiliary equipment in discrete manufacturing plants. The popular twin-model construction method based on a single type of equipment cannot meet the demand for rapid construction and high-quality model mapping in large discrete manufacturing plants. This paper proposes a strategy for developing a digital twin polymorphic model (DTPM) for discrete manufacturing workshops to meet complex manufacturing business scenarios, improve the richness of digital twin model varieties, construction efficiency and intelligence, and form an efficient equipment model construction method. The complete element information and real-time dynamic data of the minimal component unit (Functional Components, FC) of DTPM are clustered and analyzed. In addition, properties of the functional component information model are characterized from several dimensions, such as geometry, physics, and behavior. Furthermore, the FC with highly concentrated primary components is established based on the object-oriented derivation inheritance and attribute reuse hybrid drive technique. FC drastically reduces the duration of the digital twin model development process through encapsulation, inheritance, polymorphism, and other technologies. On this premise, the DTPM construction method that deeply decouples the physical structure and functional methods is proposed. DTPM integrates adaptive information interaction technology to accomplish intelligent data connection, dynamic data updating, and digitally accurate mapping of static-dynamic-virtual multidimensional models in discrete production workshops. Lastly, the method's validity is confirmed by creating a large discrete production workplace. The results indicate that the proposed technique may significantly enhance the model variety and building efficiency of large-scale digital twin workshop systems.

ZPasteurAIzer: An AI-Enabled Solution for Product Quality Monitoring in Tunnel Pasteurization Machines

In the food and beverage industry, many foods, beers, and soft drinks need to be pasteurized in order to minimize the effect of micro-organisms on the physical stability, quality, and flavour of the product. Although modern tunnel pasteurizers provide integrated solutions for precise process monitoring and control, a great number of packaging plants continue to operate with legacy pasteurizers that require irregular manual measurements to be performed by shop floor operators in order to monitor the process. In this context, the present paper presents zPasteurAIzer, an end-to-end system that provides real-time quality monitoring for legacy tunnel pasteurization machines and constitutes a low-cost alternative to replacement or the upgrading of installed equipment by leveraging IoT technologies and AI-enabled virtual sensing techniques. We share details on the design and implementation of the system, which is based on a microservice-oriented architecture and includes functionalities such as configuration of the pasteurizer machine, data acquisition, and preprocessing methodology as well as machine learning-based estimation and live dashboard monitoring of the process parameters. Experimental work has been conducted in a real-world use case at a large brewing manufacturing plant in Greece, and the results indicate the value and potential of the proposed system.

Solar Power Potential from Industrial Buildings and Impact on Electricity Supply in Bangladesh

Bangladesh has a rapidly increasing population and coupled with healthy economic growth, is resulting in a rising energy demand. The country also aims to increase its renewable share of electricity to 10% by 2030. However, due to limited wind resources, solar energy seems to be most appropriate to deliver such a target. However, in a land-scarce country, this presents a major challenge, which this work aims to partially address. Being a globally leading producer of commodities, Bangladesh has a considerable number of large manufacturing plants with appropriate roofs that could be used for deploying solar energy conversion systems at scale. A methodology is presented which identified and assessed 6045 such plants, which have roof areas ranging from 100 m2 to 50,000 m2, and modelled the deployment of solar photovoltaic (PV) technology that can provide power through site available grid infrastructure. Such deployment takes advantage of net metering regulations to enhance the case for such power generation. A techno-economic assessment was also presented, addressing how such utilisation can support the 10% renewables target of Bangladesh without impacting scarce lands. The results showed that around 7.4 GWp of PV capacity can be achieved on such roofs with a corresponding annual electricity generation of 11 TWh. This represents more than 6% of Bangladesh’s current electricity consumption and more than half of the 2030 target. Furthermore, the deployment will save 13,000 acres of farmland, as well as providing power through site available grid infrastructure saving on investment if the systems are deployed on land. These results are likely to influence policy to support the presented proposition, not only in terms of increasing the renewable energy share in the country’s electricity supply mix but also in conserving much-needed land for agriculture.

Legacy and emerging airborne per- and polyfluoroalkyl substances (PFAS) collected on PM2.5 filters in close proximity to a fluoropolymer manufacturing facility.

Large fluoropolymer manufacturing facilities are major known sources of per- and polyfluoroalkyl substances (PFAS), many of which accumulate in groundwater, surface water, crops, wildlife, and people. Prior studies have measured high PFAS concentrations in groundwater, drinking water, soil, as well as dry and wet deposition near fluoropolymer facilities; however, much less is known about near-source PFAS air concentrations. We measured airborne PFAS on PM2.5 filters in close proximity to a major fluoropolymer manufacturing facility (Chemours' Fayetteville Works) located near Fayetteville, North Carolina, USA. Weekly PM2.5 filter samples collected over a six-month field campaign using high-volume air samplers at locations 3.7 km apart, north-northeast and south-southwest of the facility were analyzed for thirty-four targeted ionic PFAS species by liquid chromatography coupled to electrospray ionization tandem mass spectrometry. Twelve emerging and ten legacy PFAS compounds were detected. Thirteen PFAS were found at higher concentrations in these nearfield samples than at regional background sites, suggesting a local source for these compounds. Five emerging and five legacy PFAS compounds had maximum concentrations exceeding 1 pg m-3. PFBA, PFHxA, PFHxDA, PFOS, PMPA, NVHOS, PFO5DoA, and Nafion BP1 contributed the most to the total (legacy + emerging) PFAS concentration (86%). Six PFAS, specifically PFBA, PFOS, PFO5DoA, Nafion BP1, Nafion BP2, and Nafion BP4, provide a consistent representative profile of elevated species across the two sites (with detection frequency >50%). To our knowledge, this is the first study to report both legacy and emerging ionic PFAS in air in close proximity to a U.S. fluoropolymer manufacturing facility.

Quality improvement study into the effectiveness of the semi-custom, prefabricated shoe insert program (Quadrastep System) at reducing complaints of discomfort in an industrial setting.

A common source of reduced productivity and lost work time in the industrial setting is musculoskeletal discomfort in the feet, knees, hips, and low back. Even when working identical job posts, these symptoms can vary widely between employees, and could potentially be caused by intrinsic foot biomechanics coupled with long-term standing activities. Therefore, to prevent injury and reduce daily discomfort, onesize-fits-all approaches such as anti-fatigue mats or off-the-shelf shoe insoles may be less effective than treating each employee’s specific biomechanical traits. The Quadrastep System is a prefabricated, semi-custom shoe insert system that bridges the gap between more expensive, fully customized orthotics and off-the-shelf options. We studied the effectiveness of the system in a large manufacturing plant by assessing and providing Quadrastep inserts to 28 volunteers. After 2 months of daily wear, 94% of these volunteers said they received some benefit from the inserts, while 52% reported full resolution of daily symptoms.

Propagation and Ampli cation of Local Productivity Spillovers

This paper shows that local productivity spillovers propagate throughout the economy through the plant-level networks of multi-region firms. Using confidential Census plant-level data, we show that large manufacturing plant openings not only raise the productivity of local plants but also of distant plants hundreds of miles away, which belong to multi-region firms that are exposed to the local productivity spillover through one of their plants. To quantify the significance of plant-level networks for the propagation and amplification of local productivity shocks, we develop and estimate a quantitative spatial model in which plants of multi-region firms are linked through shared knowledge. Our model features heterogeneous regions, which interact through goods trade and labor markets, as well as within-location, across-plant heterogeneity in productivity, wages, and employment. Counterfactual exercises show that while knowledge sharing through plant-level networks amplifies the aggregate effects of local productivity shocks, it widens economic disparities between individual workers and regions in the economy. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Cognitive and metabolic workload assessment techniques: A review in automotive manufacturing context

AbstractErgonomics assessment in the automotive industry has, to date, focused mainly on physical ergonomics, for example, manual handling and posture. However, workload and, in particular, metabolic and cognitive workload, contributes to worker efficiency but has not received sufficient attention to yield practical guidance for industry. Successful workload assessment requires in‐depth understanding of the context in which it will be conducted and of the various assessment techniques which will be applied, with consideration given to factors such as feasibility, resources, and skill of the assessor. These requirements are met with challenges within large and complex organizations and are often dealt with in a piecemeal and isolated matter (i.e., reactive workload assessment). The present paper explores these challenges within the automotive manufacturing industry and aims to develop a decision matrix to guide effective selection of workload assessment techniques focused on metabolic and cognitive demands. It also presents the requirements for time, equipment, and knowledge to implement these techniques as part of a participatory ergonomics approach. Early findings suggest that most assessment techniques reviewed require further development, for example, to establish the acceptance criteria for the specific workload scenario. However, five methods (Garg, Borg RPE, IPAQ, SWAT, and NASA‐TLX) are ready to use in certain applications. Ultimately, the findings suggest that it is possible to implement a participatory workload evaluation program within large and complex manufacturing plants.

A Hybrid Neutrosophic-Grey Analytic Hierarchy Process Method: Decision-Making Modelling in Uncertain Environments

The analytic hierarchy process (AHP) is recognised as one of the most commonly applied methods in the multiple attribute decision-making (MADM) literature. In the AHP, encompassing uncertainty feature necessitates using suitable uncertainty theories, since dealing efficiently with uncertainty in subjective judgements is of great importance in real-world decision-making problems. The neutrosophic set (NS) theory and grey systems are two reliable uncertainty theories which can bring considerable benefits to uncertain decision-making. The aim of this study is to improve uncertain decision-making by incorporating advantages of the NS and grey systems theories with the AHP in investigating sustainability through agility readiness evaluation in large manufacturing plants. This study pioneers a combined neutrosophic-grey AHP (NG-AHP) method for uncertain decision-making modelling. The applicability of the hybrid NG-AHP method is shown in an illustrative real-case study for agility evaluations in the Iranian steel industry. The computational results indicate the effectiveness of the proposed method in adequately capturing uncertainty in the subjective judgements of decision makers. In addition, the results verify the significance of the research in group decision-making under uncertainty. The practical outcome reveals that, to become a more sustainable agile steel producer in the case country, they should first focus on the “organisation management agility” as the most significant criterion in the assessment followed by “manufacturing process agility,” “product design agility,” “integration of information system,” and “partnership formation capability,” respectively.

The relationship between chronotypes and musculoskeletal problems in male automobile manufacturing workers.

BackgroundPrevious studies have shown that morning types are less sensitive to pain. This study aimed to examine the relationship between chronotypes and musculoskeletal problems in workers with musculoskeletal burdens at work.MethodsThis cross-sectional study included 119 male production workers from a large automobile manufacturing plant. All the participants worked 2 shifts and worked on the automobile assembly line. Data were obtained using structured questionnaires, including the reduced Morningness-Eveningness Questionnaire (rMEQ), and musculoskeletal symptom questionnaire. Participants with an rMEQ score of 18 points or more were defined as morning-type workers (MTWs). Participants whose scores were less than 18 points were defined as neither-type workers (NTWs).ResultsThe arithmetic mean age was 51.8 ± 5.3 years. MTWs and NTWs accounted for 35.3% and 64.7% of the total participants, respectively. Evening- and intermediate-type workers accounted form 6.7% and 58.0% of the participants, respectively. There was no significant difference in the health indicators when the MTW and NTW groups were compared. However, the musculoskeletal symptom questionnaire demonstrated a significant difference between the MTW and NTW groups. In the preceding year, the MTW group had significantly lower musculoskeletal pain and treatment ratios compared to the NTW group (35.7% vs. 62.3%, p = 0.005 and 14.3% vs. 32.5%, p = 0.031, respectively). After adjusting for variables, the odds ratio (OR) for musculoskeletal pain was significantly higher in the NTW group than in the MTW group (OR, 3.112; 95% confidence interval, 1.285–7.535; p = 0.012).ConclusionsIn this study, the musculoskeletal pain ratio was significantly lower for MTWs when compared to NTWs. Chronotypes could play an important role in work-related musculoskeletal disorders. Further, larger-scale, follow-up studies on chronotypes are required to assist in the prevention of musculoskeletal disorders in future.

Propagation and Amplification of Local Productivity Spillovers

This paper shows that local productivity spillovers propagate throughout the economy through the plant-level networks of multi-region firms. Using confidential Census plant-level data, we show that large manufacturing plant openings not only raise the productivity of local plants but also of distant plants hundreds of miles away, which belong to multi-region firms that are exposed to the local productivity spillover through one of their plants. To quantify the significance of plant-level networks for the propagation and amplification of local productivity shocks, we develop and estimate a quantitative spatial model in which plants of multi-region firms are linked through shared knowledge. Our model features heterogeneous regions, which interact through goods trade and labor markets, as well as within-location, across-plant heterogeneity in productivity, wages, and employment. Counterfactual exercises show that while knowledge sharing through plant-level networks amplifies the aggregate effects of local productivity shocks, it widens economic disparities between individual workers and regions in the economy.

The Toxic Legacy of an Industry and it’s Impacts on a Native American Tribe

From the early 1960s through the late 1970s, millions of gallons of paint sludge and other toxic materials were dumped by a large car manufacturing plant into abandoned mines, forested areas, and lands near homes in Ringwood, NJ. As a result, upper Ringwood became riddled with toxic metals in the soil, water and air. This placed a large environmental burden on the people who have lived on this land for generations, the Ramapough Lenape Turtle Clan Nation. Samples of soil, water, plants, and fish from this partially-remediated 500 acre Superfund site (from community-identified areas) were collected by citizen scientists and NYU graduate assistants. Soil samples were collected at different sites throughout upper Ringwood and analyzed for metal contents using a XRF and ICP-OES. Additionally, drinking water samples were collected, at different timepoints, from a local church and tested for metals concentration using an ICP-MS. Results showed that both As and Pb were found in several different soil samples collected around the Ringwood church, at levels exceeding the NJ soil standards of 19 and 400 mg/kg, respectively. Additionally, Pb levels - exceeding the national and federal standard of 15 ppb - were found in drinking water from the church, depending on the faucets tested. As Ramapough children play at the Church area; the Tribes’ tradition of growing their own food; and the fact that both heavy metals can cause acute and chronic diseases, the results were quickly reported back to the community, local governing body and media. These never-before identified contaminated water findings has led to the decision to switch the church water source from a local (previously-untested well) to the municipal water supply. This study demonstrates the importance of community-academic partnerships and citizen science for protecting the environmental health of marginalized populations.This study is supported by NYU NIEHS Center ES-000260-5.

A framework for analyzing how context influences lean leadership

PurposeAlthough leadership in lean systems is influenced by context, the mechanisms linking contextual factors (CFs) to leadership have not been explored. This study aims to present a framework for analyzing how context influences lean leadership competencies (LLCs).Design/methodology/approachThe framework’s design was based on insights from literature and refined through an empirical study of a large manufacturing plant formally committed to lean. The evolution of CFs over time was monitored in this study, allowing for analyzing how these triggered the need for using LLCs.FindingsThe framework proved to be useful for as follows: the assessment of LLCs in different hierarchical levels; the analysis of how CFs and LLCs interact in specific “leadership events”; and the identification of improvement opportunities for supporting leadership. Four design propositions emerged from the empirical study, offering complimentary guidance for using the framework.Research limitations/implicationsThe framework was tested in one company, and therefore generalizations about its effectiveness need further applications.Practical implicationsThe framework may be used fully or partly by practitioners. For instance, the assessment of LLCs can be used as a standalone tool according to the specific needs of practitioners. Also, by producing rich descriptions of LLCs and CFs, the framework may inform lean leadership development programs.Originality/valueThe framework allows for a systematic analysis of how a broad range of CFs influence LLCs, thus operationalizing an idea that so far has been discussed mostly on a theoretical level.

A Qualitative Exploration of Shift Work and Employee Well-Being in the US Manufacturing Environment.

Describe manufacturing workers' perceptions of the effect of shift work, following the Framework for Worker Well-Being. Eight focus groups and 43 interviews were conducted across four large manufacturing plants. Thematic analysis was used to analyze the data within each of the five domains of the Framework: physical environment and safety climate; workplace policies and culture; health status; work evaluation and experience; and home, community, and society. Respondents described shift work as detrimental to well-being across four of the five Framework domains. The exception was in the workplace policies and culture domain, where some respondents described shift work as necessary, fair, and financially beneficial. Shift work negatively influences worker well-being in a holistic way. Employers could consider reconfiguring workplace wellness benefits to transcend the boundaries of the workplace and better support workers and their families.

Birds, Birds, Birds: Co‐Worker Similarity, Workplace Diversity and Job Switches

AbstractWe investigate how the demographic composition of the workforce along the sex, nationality, education, age and tenure dimensions affects job switches. Fitting duration models for workers’ job‐to‐job turnover rate that control for workplace fixed effects in a representative sample of large manufacturing plants in Germany during 1975–2016, we find that larger co‐worker similarity in all five dimensions substantially depresses job‐to‐job moves, whereas workplace diversity is of limited importance. In line with conventional wisdom, which has that birds of a feather flock together, our interpretation of the results is that workers prefer having co‐workers of their kind and place less value on diverse workplaces.

Job Reallocation Dynamics in India: Evidence from Large Manufacturing Plants

AbstractThe paper contributes to the limited literature on job reallocation dynamics in Indian manufacturing. The study uses annual data from the Annual Survey of Industries (ASI) for the years 2000–01 to 2015–16. The study finds job reallocation in India to be quite high compared to flexible labour markets such as the United States and Canada. Gross job reallocation shows a rising trend over time, which is driven partially by the increasing share of contract workers in the workforce. There is heterogeneity in the job reallocation dynamics across job types. This is evident in the relative importance of the different job types as plants adjust to permanent and temporary changes in demand. Labour regulations also play an important role in such a process. Finally, in contrast to the evidence for the United States and the United Kingdom, our study found firm evidence to reject the hypothesis that job reallocation is countercyclical in India.

Next-generation sequencing reveals predominant bacterial communities during fermentation of Thai fish sauce in large manufacturing plants

Bacterial communities in fish sauce, at different fermentation phases, from two large manufacturing plants (Factories MC and SQ) in Thailand, were studied. The bacterial microbiota in a fish sauce mash of >12 months were examined by 16S rRNA next-generation sequencing. We revealed the presence of 7 phyla, 14 classes, 21 orders, 31 families, and 45 genera of bacteria in the fish sauce. Bacterial communities in the sauces differed across the two factories. In Factory MC, Halanaerobium sp. was the initial dominant genus, which gradually decreased while Lentibacillus sp., Halomonas sp., and Tetragenococcus sp. began to appear in the middle phase. Diversity was the highest in the late fermentation phase. On the contrary, in Factory SQ, high diversity was observed right from the early phase till the late fermentation phase. The bacterial communities varied at different stages of fermentation as well. The most common genera were Peptostreptococcus sp., Peptoniphilus sp., Gallicola sp., Fusobacterium sp., Halanaerobium sp., and Vagococcus sp.. Alpha and beta diversity within the bacterial communities in fish sauce from the factories was also calculated. This is the first report revealing bacterial communities during industrial fermentation of Thai fish sauce. The source of raw materials and bacterial microbiota in the fermentation tank influenced the type of bacteria present throughout the process, and consequently affected the unique product characteristics.

Redistributing food manufacturing: models for the creation and operation of responsive and agile production networks

The food industry is a mature industry where its profit margins are thin and its R&D failure rate for new products is substantial. Both facts indicate that decent return on development investment cannot be provided and that the food industry cannot still rely on its traditional way of thinking and innovating. New product development cycles should involve not only the product itself but also the entire manufacturing and distribution network. Hence, collaborative manufacturing and servitization models are key elements for the rapid transformation of the new food industry. Moreover, recent developments in technology have the potential to shift manufacturing production away from large scale manufacturing plants to a network of distributed, smaller scale localized and customizable manufacturing facilities. Such a network is the crucial enabler for the on-demand manufacture of new or even, existing food products to rapidly respond to the consumers´ demands.

Understanding the main organisational antecedents of employee participation in continuous improvement

Purpose Companies use continuous improvement (CI) as a strategy to achieve business excellence and innovation. Yet CI initiatives fail mostly due to a lack of employee engagement. The paper aims to discuss this issue. Design/methodology/approach Based on the CI literature and the technology acceptance model (TAM), a comprehensive model called continuous improvement acceptance mode (CIAM) was developed to understand the main organisational antecedents that predict employee intention to participate in CI. The CIAM is based on structural equation modelling using partial least squares and it was validated in a large manufacturing plant in Europe. Findings Emulating the findings of the TAM, this study shows that employee intention to participate can be predicted by two variables called ease of participating and usefulness of participating. The CIAM then relates these constructs with relevant CI enablers found in the CI literature. Practical implications The CIAM could help academics and practitioners to better understand employee participation in CI activities, allowing CI systems to be better designed and achieve long-term sustainability. Originality/value The CIAM presents new variables and interactions that help to understand employee participation in CI activities. Some of these variables and interactions have received scant attention in the CI literature and thus they are worth investigating in greater depth in the future.

Birds, Birds, Birds: Co-Worker Similarity, Workplace Diversity, and Voluntary Turnover

We investigate how the demographic composition of the workforce along the sex, nationality, education, age, and tenure dimension affects voluntary turnover. Fitting duration models for workers' job-to-job moves that control for workplace fixed effects in a representative sample of large manufacturing plants in Germany during 1975–2016, we find that larger co-worker similarity in all five dimensions substantially depresses voluntary turnover whereas workplace diversity is of limited importance. In line with conventional wisdom, which has that birds of one feather flock together, our results suggest that workers prefer having co-workers of their kind and place less value on diverse workplaces.