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The demand for distributed manufacturing systems (DMS) in the manufacturing sector has notably gained vast popularity as a suitable choice to accomplish sustainability benefits. Manufacturing companies are bound to face critical barriers in their pursuit of sustainability goals. However, the extent to which the DMS attributes relate to sustainable performance and impact on critical barriers to sustainability is considerably unknown. To help close this gap, this study proposes a methodology to determine the relative importance of sustainability barriers, the influence of DMS on these barriers, and the relationship between DMS attributes and sustainable performance. Drawing upon a rich data pool from the Chinese manufacturing industry, the Best-Worst Method (BWM) is used to investigate the relative importance of the sustainability barriers and determine how the DMS attributes influence these barriers and relate to sustainability. The study findings show that ‘organizational barriers’ are the most severe barriers and indicate that ‘reduced carbon emissions’ has the highest impact on ‘organizational’ and ‘socio-cultural barriers’ whereas ‘public approval’ has the highest impact on ‘organizational barriers. The results infer that ‘reduction of carbon emission’ is the DMS strategy strongly linked to improved sustainable performance. Hence, the results can offer in-depth insight to decision-makers, practitioners, and regulatory bodies on the criticality of the barriers and the influence of DMS attributes on the sustainability barriers and improve sustainable performance for increased global competitiveness. Moreover, our study offers a solid foundation for further studies on the link between DMS and sustainable performance.

Existing research has produced mixed, inconclusive, and even conflicting findings on the impact of open innovation (OI) on innovation output. This article takes a meta-analysis approach, systematically reviews the existent literature to identify the main contextual factors, and statistically tests the significance of these factors in influencing the effect of OI on innovation output. Based on the data of 139 studies published by 2020, this article demonstrates that 1) OI has a stronger effect on innovation output in coupled OI (a combination of inbound and outbound OI) than the inbound or outbound OI alone; 2) OI has a stronger effect on innovation output in developing than developed countries; 3) OI has a stronger effect on innovation output at subfirm than firm level; and 4) OI has a stronger effect on innovation output in service than manufacturing industries. The findings have important implications for managers, researchers, and policy-makers.

As a typical mechatronics system, the battery manufacturing chain becomes a hot research topic because it directly determines electrode quality, further affecting manufactured battery performance. Due to the complexity of battery manufacturing, an effective sensitivity analysis solution that could quantify variable importance or correlations and explore impact variables toward resulting the electrode quality is urgently needed. This article scrutinizes the effects of component parameters from the mixing stage on the manufactured results of Li-ion battery electrode via classification modeling. Specifically, an effective RUBoost-based ensemble learning framework is proposed to compensate for class imbalance issue and well classify three key quality indicators including the electronic conductivity, thickness, and half-cell capacity for both LiFePO $_4$- and Li$_4$ Ti$_5$O$_{12}$-based electrode. Experimental results reveal that the proposed models could well handle the class imbalance issues and accurately classify/predict the qualities of the manufactured electrode. Moreover, the importance weights of variables and the correlations of variable pairs could be effectively quantified. Due to the superiority in terms of accuracy, interpretability, and data-driven nature, the proposed ensemble learning approach could not only help to conduct reliable multiclassification of manufactured electrode but also benefit smarter battery manufacturing.

Industry 4.0 (I4) technologies are gaining increased importance in the manufacturing industry, as they can provide several benefits such as an increase in efficiency, lower costs, higher revenues, etc. This article empirically examines the critical success factors (CSF) for implementing I4 technologies in Indian automotive manufacturing industry. In this regard, CSF and performance outcomes of I4 technologies are identified from published literature. The relationships between CSF and performance outcomes are then examined by regression analysis. The results indicate that “Data governance” is the most critical factor, as it affects all the four performance outcomes (operational, product, economic, and responsiveness). Similarly, “Legal aspects” affects three out of the four performance outcomes (operational, product, and economic performance), while “Collaboration and teamwork” affects only operational performance and responsiveness. The study provides an understanding of factors which are critical in achieving performance outcomes about I4 technologies in the automotive manufacturing industry. The findings can also help automotive manufacturing firms toward an informed decision making in terms of various strategies required to adopt I4 technologies successfully.

The manufacturing industry plays a big role for pollution. To reduce impact of envoirmental pollution we have to concentrate on manufacturing sector. For the better manufacturing process which including controlling environmental pollution. This is motive of green manufacturing. Environmental pollution is happens due to friction between material and tool as well as cutting fluid. Considering cutting fluid as prime parameter in manufacturing. Most of the industries are taking care regarding selection of cutting fluid which enhances the property of cutting and reduces the environmental pollution. Temperature is main parameter while cutting as increases in temperature it will effects on surface roughness and accuracy of output with addition of tool failure. To reduce the effect of tool failure there is need of cooling system is needed. By comparing mineral oil with vegetable oil with respect to pollution giving better result. Various vegetable oils are used coconut oil, canola oil, sesame oil and palm oil in machining. Wettability and thermal conductivity will improve by addition of nanomaterials like MoS2, ZrO2, Al2O3, ZnO, TiO2, TiC-CO, Y-Zr2O3 etc. in green cutting fluids. More research work is needed to analyze effects of nanomaterials concentration in vegetable oils for better green cutting fluid development

PT. XYZ is a manufacturing company that produces nata de coco pieces. Consumers of the product nata de coco pieces of food businesses such as food PT.Garuda Sidoarjo, PT. Holy Sinar Mas, PT. Borobudur Semarang and others. PT. XYZ has two types of contract supplier and the supplier is not a contract. Currently, the company in the selection of suppliers do not contract into supplier contracts sometimes have trouble. Terebut difficulties occurred because of the detailed criteria that can be used for the selection of suppliers. So in this study will berusahaan find criteria that influence supplier selection. The data in this study using the method Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). In addition, models that have been made will be implemented into a Decision Support System (DSS). The criteria that can mempengeruhi supplier selection is the sum total, the number of total quality one, a total of two quality, the total number of nata broken, the number of deliveries the maximum, the maximum number of quality one, the maximum number of two qualities, the maximum amount is broken, the number of deliveries at a minimum, the number of minimum quality one, the minimum number two quality, the minimum amount is broken, regularity, quality price and the price of the quality of the two. In addition, based on test results Decision Support System (DSS), which has made the conclusion that the system that has been created can be used later by PT. XYZ.

Within the context of a theoretical model where an increase in the proportion of foreign-invested firms is interpreted as increase in foreign direct investment (FDI), this paper shows that, through its impact on firm capability and revenue, FDI can affect the quality of goods produced by domestic firms in host economies. We show that, in the presence of positive productivity spillovers, an increase in the proportion of foreign-invested firms lowers the cut-off capability of domestic firms, which allows some relatively inefficient domestic firms to enter the industry thereby contributing to a decrease in product quality. An increase in the proportion of foreign-invested firms affects firm revenue through two channels. On the one hand, an increase in the proportion of foreign-invested firms enhances productivity, which contributes to an increase in firm revenue. On the other hand, entry of new domestic firms also increases the level of competition within the industry, which puts a downward pressure on firm revenue. We conclude that, in the presence of positive productivity spillovers, an increase in FDI decreases the quality of goods produced by domestic firms in host economies only if its impact on firm revenue is sufficiently small (or negative). Using data from China’s beverage manufacturing industry, employing the nonlinear seemingly unrelated regression technique on firm level data and without explicitly measuring quality, we estimate the impact of an increase in the proportion of foreign-invested firms on the product quality of domestic firms. Our empirical analysis suggests that a 1% increase in the proportion of foreign-invested firms decreases the product quality of domestic firms by more than 0.6259%.

Growing population and depleting resources are forcing the manufacturers to become more competent and sustainable. Customers are becoming more and more informed about the product they consume, and therefore, manufacturers need to be flexible and open to new changes taking place. Big Data Analytics (BDA) is one such technology that has transformed the manufacturing sector. Organizations have now become more flexible with regards to their processes and, at the same time, have also improved their product quality. Here in this paper, we have analyzed various advantages of Big Data that manufacturing organizations can exploit for their betterment. We have also discussed examples of certain leading manufacturers and how they can lead to big data-enabled manufacturing. Lastly, we discuss certain shortcomings that need to be addressed to make big data analytics viable for organizations of all sorts and not just for top manufacturers.

The manufacturing industry in Iraq has faced, during the time stages, several obstacles that have had devastating effects on the Iraqi economy. These obstacles are represented by political events and wars that have led to the depletion of most human and material resources and the suspension of most vital industrial facilities from working, And the occurrence of this major deviation in the process of economic development, For the same reasons, the contributions of the manufacturing sector to the gross domestic product varied fluctuatingly, indicating instability in the growth rates of this sector, On the other hand, the supremacy of the belief that the dominance of oil resources as a main source for creating economic growth and achieving a high level of prosperity placed the manufacturing sector a place of great neglect. The result is that growth in this sector has become distorted in light of the heavy dependence on the oil sector. This study aims to estimate the production functions in the manufacturing industry in Iraq. Through which the existing production relations in this industry can be analyzed, And the extent of the possibility of substituting the factors of production, and measuring the flexibility of production for the factor of labor and capital, and marginal productivity.

The present for supporting in market any industries need to bring the balance among ecological, social viewpoints and efficient. Environmental friendly machining e.g. high pressure cooling, MQL machining, cryogenic machining, dry machining is one of the latest approach which is economical and also eco-friendly that improve machinability. In present article main focus on understanding of environmental friendly machining techniques and investigate various experiences from the past writing which can help the better appropriation of ecological friendly machining approach. For study and examination of environmental friendly machining approach, roughly 100 papers are chosen. They chose articles are ordered dependent on climate of machining, year, diaries, distributor, and ecological friendly machining approach measurements. After the literature survey it was observed that in metal cutting operation heat are generated in the cutting zone due to tool chip interface so quality of surface finish are poor and tool wear. In any manufacturing industries two factors play important role in term of quality e.g. surface roughness and tool wear so in this situation some techniques are need which is environmental friendly and also improve machinability. So finally, it was observed that environmental friendly machining techniques are cost effective and eco-friendly machining compared to other convention machining approach. The main motives of this paper that studies and encourage environmental friendly machining approach.

To experience seamless adoption of future industry 4.0, it is imperative to investigate its existing roadblocks and success factors in the Indian manufacturing context. Striking similarities among diverse researches highlight the importance of the cyber-physical system assuring many benefits to the manufacturing sector. Many studies concluded that sooner or later, all manufacturing companies will evolve by penetrating industry 4.0 technologies in their enterprise activities. There is a possibility of negative consequences on business functions if top management remains unprepared to assess roadblocks to these future technologies' adoption. Identification of roadblocks is the first and foremost thing industrial policymakers should focus on. This research enlists the stumbling blocks for industry 4.0 technologies' adoption that manufacturing industries may encounter by reviewing the latest literature and ranks them using VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) methodology by consulting five experienced Indian industrial authorities. Weightage to each industrial experts' input is decided by the entropy method. Results indicate that “Skilled workers scarcity,” “Internal employee resistance,” “Worries about cyber security,” and “Inadequate knowledge of/from exterior agencies” are the top four barriers to the incorporation of industry 4.0 technologies in the Indian manufacturing context while “Lack of knowledge about enabling technology solutions” secured lower position. The robustness of the output was checked by carrying out a sensitivity analysis with varying weights. The approach adopted in this study will be helpful for industrial authorities to concentrate their efforts in tackling the most critical barriers. This research will aid industrial decision-makers in remaining proactive during the industrial technology adoption transition.

PurposeRecent technological and social changes have challenged manufacturing firms to remain competitive in increasingly dynamic markets. A way of facing these challenges is to foster organizational structures that encourage creativity. Although the general importance of organizational creativity for market success is undeniable, few studies on manufacturing firms have provided a nuanced view of how this relationship is affected by firm-external factors (e.g. different levels of market dynamism) and whether and how this leads to greater market success.Design/methodology/approachThis research uses survey data from 255 chief executive officers (CEOs) and top managers of manufacturing firms in Germany. The authors performed different regression analyses to test for direct, mediation, moderation and moderated mediation effects.FindingsThe findings show that, in highly dynamic markets, organizational support for creativity indeed helps manufacturing firms to remain competitive by positively influencing firms' innovation performance, which subsequently results in improved market performance. By contrast, in markets with low dynamism, organizational support for creativity has no impact on firms' innovation and market performance.Research limitations/implicationsFrom a theoretical perspective, this study introduces market dynamism as a novel, so-far underexplored firm-external factor that moderates the relationship between organizational support for creativity and innovation and market performance. This research thus enhances the understanding of the dynamics of organizational creativity and its effects on innovation and market performance in an organizational context of manufacturing firms.Practical implicationsIn general, this research emphasizes the importance of establishing a creativity-supporting environment to enhance innovation and market performance. Most importantly, this relationship depends on whether firms are active in highly dynamic or stable markets. Managers should thus consider the level of (future) market dynamism when making decisions about creativity-supporting work environments.Originality/valueThis research provides novel insights into how organizational support for creativity influences innovation and market performance in the manufacturing industry and introduces market dynamism as an important moderating factor.

The biopharmaceutical industry is evolving with a shift in focus from recombinant proteins and antibodies towards more complex cell and gene therapies. To be competitive globally, biomanufacturers need to focus on aligning with global standards with regard to drug quality, reducing manufacturing failures and delivering drugs to market quickly. Building these capabilities requires a multifaceted approach that includes improvements in operations, quality compliance, and control strategies. To address these needs, the US Pharmacopeia (USP), the Department of Biotechnology (DBT) India, and the Confederation of Indian Industry (CII) held a symposium to discuss the requirements and gaps in the biotechnology and pharmaceutical sectors in India and other developing countries. A panel of experts from academia, manufacturing, and governmental agencies identified several drivers needed for capability building, including a skilled workforce, public–private partnerships, advanced manufacturing technologies, novel biologics, and favorable policies. This article summarizes the recommendations put forward by this panel.

Changes in a product are necessary to guarantee high quality product and to remain competitive in the market. Engineering Change Management process ensures planning and implementation of changes effectively. Product design changes may be required in each step of product life cycle from its design to decline phase. Different tools are developed to study change propagation impact. Product architecture and change propagation path selection are the main focus areas found in methodologies developed for change management in recent years. Still, the manufacturing industry is facing challenges to control changes in implementation phase. A case study is conducted in an automotive company to understand perceived effect of product design change in manufacturing environment. Results of case study draws attention towards concerns reported, starting from raw material planning to disposition of changed part and the need for prediction of change in implementation phase across the functions, as well as in complete supply chain of automotive industry. Change propagation tools can be, if needed, extended from design phase to manufacturing environment.

Purpose: The main aim of the article is to present the issue of the economic performance of logistical processes and the results of own research on their calculation in Polish manufacturing companies. Approach/Methodology/Design: The undertaken research issues and the set goal determined the choice of research methods, such as critical literature review, questionnaire research of Polish production companies, analysis and synthesis methods. Findings: A reliable system for measuring the economic performance of the company's logistical processes and the valuation of individual types of resources is undoubtedly a condition for the success of a manufacturing company's policy. Practical Implications: It was established that for each type of resource (logistics infrastructure, material and financial resources and human capital) there is a significant dependence of its valuation depending on the calculation of the economic performance of logistical processes.The results can be used to develop a long-term strategy on the development of Polish production companies. Originality/Value: The proposed solutions are to contribute to the development of Polish production companies., peer-reviewed

This paper sketches the major sociological transformations of Japanese society of the last three decades, 1990–2020, which can be regarded as a crucial turning point in Japan’s history. It first examines the marked paradigm changes that have occurred in Japanese studies. The paper then endeavours to unravel how such alterations reflect the structural changes caused by the penetration of neoliberalism, the decline of the manufacturing industry, and the expansion of cultural capitalism. After illustrating how these forces have fragmented social relations, the paper ends with a description of how Japanese society is becoming increasingly amorphous in its social structures and value orientations. The paper attempts to cast the shifts of these three decades into relief against the background of the previous three decades, 1960–1989, when Japan enjoyed spectacular economic growth.

The manufacturing industry is the biggest contributor to the gross domestic product of Indonesia. The cost of debt is one of the factors for manufacturing companies in carrying out their operations. Lowering the cost of debt could attract manufacturing companies to raise funds through debt that will help the companies generate profit. This research figures out the impact of factors that may affect the cost of debt. This study is quantitative research that uses multiple regression as statistical analysis to test the hypotheses by using E-views 10 as a tool. The data population is manufacturing firms in Indonesia and samples are manufacturing firms listed on Indonesia Stock Exchange for 2015-2019. The results show that institutional ownership, debt to equity ratio, and interest coverage ratio impact the cost of debt. While managerial ownership, firm size, and return on assets do not impact the cost of debt.

In this paper, I make use of Vietnam’s enterprise surveys to estimate markups and product quality and investigate the effects of tariff preferences under the ASEAN and ASEAN+1 free trade areas (FTA...

Purpose Over the past few decades, lean manufacturing has focussed on being customer-centred and now Lean 4.0 technologies have made it possible for manufacturers to have a deeper view of waste reduction. Technologies such as the internet of things, artificial intelligence, three-dimensional printing, robotics, real-time data, cloud computing, predictive analytics and augmented reality, are helpful to achieve Lean 4.0. This study aims to develop the conceptual understanding of Lean 4.0, related tools and linkage with Industry 4.0. Further, it provides the strategies for implementing Lean 4.0, developing lean culture and highlights the Lean 4.0 application in the manufacturing context. Design/methodology/approach This study relates to Lean 4.0 and its technologies. Prominent research is identified through Scopus, Web of Science, ScienceDirect and Google Scholar and studied as per the objective of this study. This lean revolution provides customers desire for personalisation, connectedness, high-quality and valuable products. Lean 4.0 provides valuable information on the value chain and production process. This revolution has significantly impacted refining production processes for a greater level of adaptability and cost reduction. Findings This paper is brief about Lean 4.0 and its capabilities for the reduction of waste. The authors discussed different tools used in Lean 4.0 and its relationship with Industry 4.0. The classical strategies and progressive features of Lean 4.0 for overall enhancing the manufacturing sphere are discussed diagrammatically. Finally, it identified and discussed 14 significant applications of Lean 4.0 for manufacturing industries. Originality/value This study provides a comprehensive understanding of Lean 4.0 and related tools and strategies that help the upcoming manufacturing industries.

Charles Amteme, NPM: 42150013 "Analysis of Economic Sectoral Potential in Belu Regency" under the guidance of Mr. Prof.Dr. Sirilius Seran, SE.MS as supervisor I and Mr. Frederich W. Nalle, SE.ME as supervisor II. The problem raised from this study is how the sector shifts to the economy in Belu District and whether there are leading sectors in the economy in Belu District. The objectives to be achieved in this study are to determine the Sector Shift to the economy in Belu District and to find out whether there is a superior Sector in the economy in Belu Regency. The data used in this study are secondary data obtained from the Central Statistics Agency Office in Belu Regency. The data analysis technique used is the Shift Share analysis and Klassen Typology. Based on the results of shift share analysis, the sector that has the largest national share value is the agricultural sector, while the smallest value is in the electricity and gas and clean water sectors. According to the proportional shift analysis it is known that there are six sectors in Belu Regency whose growth is slower ompared to the NTT province, namely: agriculture, mining and grazing, the manufacturing industry sector, the electricity gas and water supply sector, the hotel and restaurant trade, and the sector finance, leasing and corporate services. While the differential shift analysis is known that there are four sectors in Belu Regency that grow faster based on internal locational factors, namely: the mining and mining sector, the manufacturing sector, the electricity, gas and water supply sector and also the transportation and communication sector. Based on the results of the typology analysis, the sectors included in the developed and rapidly growing sectors are other service sectors. Meanwhile, the sectors included in the advanced but depressed sectors are the financial sector, leasing and corporate services. Sectors classified as potential or still developing sectors are: agriculture and the relatively backward or underdeveloped sectors are the mining and quarrying sector, the processing industry, gas electricity and drinking water, construction, the restaurant and hotel trade and the communication and transportation sector.

Tourism is one of the fastest-growing industries. Tourism is able to move the economy forward at the micro-level such as encouraging the informal sector and local potential while at the macro level it can increase currency transactions. In various countries, the tourism sector is able to increase domestic and foreign demands as well as to encourage transportation, hospitality, and manufacturing industries. This study examines the effect of institutional indicators on tourism in ASEAN countries during 2000-2018 under dynamic panel estimation. The number of observations was about 180, namely: time series from 2000-2018 and cross-section of 10 countries. ASEAN as one of the destinations in the world requires an increase in institutional quality to be able to compete and provide world-class tourism services. The six institutional indicators were employed such as voice and accountability, political stability and absence of violence, government effectiveness, regulatory quality, rule of law, and control of corruption. Moreover, the dynamic panel estimation was expressed by Pooled OLS and REM estimations. Interestingly, the findings show that political stability compromises the number of tourist arrivals while government effectiveness can stimulate tourist arrivals. Similarly, GDP per capita can hinder the number of tourist arrivals, while the exchange rate leads increasing of tourism arrivals. Thus, the governments in ASEAN countries can promote and cooperate together to develop tourism in the regional level. The GDP per capita of ASEAN countries should be increased, and the level of exchange rate can be maintained at a stable range. Besides, the governments should also improve the quality of institutions.

Productivity growth needs to be optimized not only to produce quality products, increase exports, and reduce dependence on imports but also to support the performance of the manufacturing sector. This study aims to determine the manufacturing industry map in Banten Province, measure manufacturing industry productivity growth, and analyze the effect of Local Content Requirement (LCR) on manufacturing industry productivity growth from 2005 to 2017 by employing the use of K-Means cluster and panel data regression analysis. For this purpose, Total Factor Productivity (TFP) is the indicator used to measure productivity growth. The LCR is known as the percentage of local raw and auxiliary materials used in the production process. According to K-Means cluster analysis results, industrial companies are grouped into three clusters with different characteristics. The result of panel data regression analysis shows that the TFP of all manufacturing industry sub-sectors has increased and was influenced by LCR, total production, domestic investment, import, and provincial minimum wage. As a result, the government should integrate the LCR and other policies, such as the Indonesian National Standard, to increase productivity growth.

Human error in manual assembly systems affects system reliability, safety and it is one of the most important causes of quality defects. Many researchers have developed methods for Human Reliability Analysis (HRA) with the aim of identifying, modeling, quantifying and reducing human error, mainly in safety-critical industries. This paper addresses human reliability analysis in assembly systems, where most of the employed workforce is currently involved. The main purpose is to systematically investigate the current state-of-the-art on this topic, analyzing and summarizing the theoretical and empirical contents, identifying patterns and research streams, informing the strengths and weakness of selected literature and so highlighting the research and practice opportunities. The results of this study show that a prospective analysis of human reliability in the manual assembly systems until now has been neglected in literature. Nevertheless, HRA methods and assembly specific methodologies and approaches found in literature can be successfully applied to assembly systems, allowing users to predict human error probability and to determine the most significant error influencing factors. Furthermore, the results highlight the role of human error in the occurrence of quality defects (rejected or reworking). This paper, therefore, contributes to the transfer of knowledge about human reliability gained in manual assembly operations, providing practitioners and researchers with a comprehensive overview of this topic and several research opportunities for future studies.

This research was conducted on the plastic manufacturing industry during the covid-19 pandemic. The purpose of this study was to examine the effect of compensation and performance appraisal on employee job satisfaction through competence as a mediating variable. The data in the study consisted of 150 populations and 109 samples in the study were employees of PT. Vindo International. Data analysis in this study used quantitative methods with the SmartPLS 3.0 test tool. Financial and non-financial compensation is part of the company's motivation to reward performance achievements. Providing appropriate compensation can provide employee job satisfaction and can trigger better performance. So that in the construction of this research a synergistic relationship is built in the provision of compensation accompanied by performance appraisals based on employee competencies, this will provide employee job satisfaction. Employee job satisfaction has an impact on performance, loyalty and awareness. All of this will shape the organizational culture to achieve company goals. The findings in this study are performance appraisals that are not based on employee competence can lead to individual subjectivity, this does not provide job satisfaction.

In post-reforms years, employment in organized manufacturing sector was much faster than pre-reform years. Growth momentum of employment has been larger than growth momentum of output. Further, since year 2000, real wages of the workers increased much faster, while per cent share of income wages in value added of industry output showed a decline. Declining wage share is a global phenomenon, not confined to a specific economy. The present paper points out that in all selected years (2006–2007, 2009–2010, 2013–2014 and 2017–2018), rise in labour productivity has increased wage disparity. It implies if wages and salaries of non-workers increase disproportionately due to rise in labour productivity in organized manufacturing factories, the wage disparity will rise. Increase in labour productivity increases average real wages during 2009–2010 and 2017–2018. Also, in 2009–2010 and 2017–2018, increase in capital labour ratio results in an increase in wage rate. Further, study also shows that average wage rate rises and wage disparity falls across the Indian states.

Every manufacturing company will strive to create the best quality products. This is also done by PT. CMSM, a steel company, is producing corrugated zinc products. In several production periods, the defective product values were still found that exceeded the tolerance limit value set at 0.5% in corrugated zinc products. These problems are, of course, very detrimental to the company, so it’s essential to control the quality of corrugated zinc products. This study aimed to determine the factors that cause product defects, propose plans to improve product quality, and provide managerial recommendations based on Six Sigma analysis. Data collection techniques are carried out through observation, interviews, and documentation. Based on the study results, it is known that DPO is 0.000885 and DPMO is 884.6028. At this time, the company is at the level of 4.64 sigma with CTQ (Critical to Quality) folded zinc sheet, cut size is not according to standard, thickness is not according to standard, uneven coating layer and perforated zinc sheet. Based on the analysis, five factors cause product defects: humans, machines, methods, materials, and the environment. To improve quality, the company should improve their quality control through 5W + 1H analysis, namely by providing training to employees, periodic machine maintenance and ensuring that the SOPs that have been made are implemented correctly and adequately. Keywords: six sigma, DMAIC, product defect, quality control, manufacturing

This paper explores the relationship between wage increase and innovation and investigates the underlying mechanisms through which wage increase affects innovation. Empirical results, based on the ...

The Covid-19 pandemic has affected all sectors, especially the health sector, worldwide. In terms of economy, sectors have experienced problems, and the pandemic has brought many economic problems. The pandemic has significantly affected the consumption trend, businesses with reduced cash flow have had to use foreign financial resources. The aim of this study is to analyze the impact of the global Covid-19 pandemic on the amount of cash loans used from banks andnon-performing loans in agriculture, manufacturing industry, hotels and restaurants, transportation, storage and communication, and education sectors. As a result of the analysis, it is seen that the amount of cash loans and non-performing loans used from the deposit banks and the entire banking system increased sectorally after the Covid-19 pandemic compared to before the pandemic.

Recently, due to the population aging and the fast development of information and communications technology (ICT), the number of laborers has remarkably decreased. This has created a demand to improve the productivity and product quality of companies and manufacturers. Besides, Smart Factories are expected to meet those requirements as consumers' needs are diversified, demanding personalized production and rapid and accurate manufacturing innovation rather than traditional manufacturing firms. The term “Smart Factory” means an intelligent factory that integrates ICT into the traditional manufacturing industry. This applies to the entire process of planning, requirement analysis, design, production, distribution, and sales. Smart Factory broadly covers level 4 areas that deal with general information technology (IT) and level 0–3 areas that deal with operational technology (OT). Thus, information covered in OT areas can cause problems not only for a company but also for its country if it is leaked to the outside world as a company’s core asset. Therefore, it is important to identify and respond to potential security threats in a Smart Factory environment. To this end, in this paper, we research the components of major Smart Factory architecture. Subsequently, we discuss security issues and problems that may occur before the establishment of a Smart Factory. Finally, we propose a Smart Factory security model and a secure response to cyberattacks to address security issues.

Los servicios de extensionismo tecnológico (SET) forman parte de políticas industriales y de innovación implementadas en diferentes países de Iberoamérica para impulsar la sostenibilidad de las industrias culturales y creativas. En base a una investigación cualitativa sobre la situación actual de este tipo de servicios en el Perú, el artículo propone priorizar cinco de ellos para promover los negocios culturales en economías emergentes como la peruana. Se sostiene que los bienes y servicios culturales tienen características económicas particulares, como la centralidad de la creatividad en los procesos productivos y la demanda impredecible. En consecuencia, el artículo explica que, para desarrollarlos mediante el extensionismo tecnológico y sus indicadores de desempeño, se requiere aplicar criterios distintos a los usados en las industrias extractivas o la manufactura.

Data-driven quality monitoring is highly demanded in practice since it enables relieving manual quality inspection of the product quality. Conventional data-driven quality monitoring is constrained by its offline characteristic thus being unable to handle streaming nature of sensory data and nonstationary environments of machine operations. Recently, there have been pioneering works of online quality monitoring taking advantage of online learning concepts in the literature, but it is still far from realization of minimum operator intervention in the quality monitoring because it calls for full supervision in labelling data samples. This paper proposes Parsimonious Network++ (ParsNet++) as an online semisupervised learning approach being able to handle extreme label scarcity in the quality monitoring task. That is, it is capable of coping with varieties of semisupervised learning conditions including random access of ground truth and infinitely delayed access of ground truth. ParsNet++ features the one-pass learning approach to deal with streaming data while characterizing elastic structure to overcome rapidly changing data distributions. That is, it is capable of initiating its learning structure from scratch with the absence of a predefined network structure where its hidden nodes can be added and discarded on the fly in respect to drifting data distributions. Furthermore, it is equipped by a feature extraction layer in terms of 1D convolutional layer extracting natural features of multivariate time-series data samples of sensors and coping well with the many-to-one label relationship, a common problem of practical quality monitoring. Rigorous numerical evaluation has been carried out using the injection molding machine and the industrial transfer molding machine from our own projects. ParsNet++ delivers highly competitive performance even compared to fully supervised competitors. National Research Foundation (NRF) Published version This project was financially supported by National Research Foundation, Republic of Singapore, under IAFPP in the AME domain (contract no. A19C1A0018).

In present business world a lot of entities tend to conduct training programs to the employees and expecting high level of performance from the employees. Hence the different kinds of training methods are used by the manufacturing sectors to train workforce. Although there are number of researches conducted in assessing the impact of training programs of manufacturing industry in other countries in Sri Lankan context research findings in this regard is limited. Therefore, the objective of the current study was to assess the impact of ‘employee on the Job Training on the performance of production assistants in Noritake Lanka (Pvt) Ltd. Matale, Sri Lanka. The independent variable and the dependent variable of this study were the level of on-the job training and the employee performance respectively. The reliability of the instruments was tested by using Cornbrash’s Alpha coefficient. The type of this study is hypothesis testing ant it was conducted in the natural setting with the minimum interference of the researcher. The study is a cross-sectional in time and the primary data were collected by using random sampling technique and sample size was 100 production assistant employees who are working in Noritake Lanka (Pvt) Ltd in Matale District. The unit analysis was at individual level. Data was collected through a structured questionnaire. The offline method was use to gather the data and the primary data set was used. The correlation and regressions methods were performed to test hypotheses and analyzed data. Finding revealed that on-the-job training has a significant impact on employee performance. Correlation analysis shows that on-the-job training has a strong positive relationship on employee performance. As a significant factor, this would mean that it is very significant to pay a high attention regarding the on-the-job training methods, because it directly affects to the performance of the employees in addition to that proper and well-structured on-the-job training are required to meet with the desired outcomes of the organization. Plenty of benefits can be obtained from on-the-job training method for the both employees and the organization.

PurposeThis study aims to explore how horizontal collaboration can help small and micro enterprises within the drink sector through the relational theory lens.Design/methodology/approachThe use of qualitative research methods, including focus groups and interviews, facilitated understanding the horizontal collaboration in micro and small companies within the Welsh brewery industry. Data collection involved conducting three focus groups and 13 interviews within the Welsh brewery sector in the UK. The collaboration phenomena were explained using the three elements of relational theory: relational rents, relational capitals and relational governance.FindingsMicro and small enterprises in the drink sector use collaborative initiatives in building new capabilities to generate relational rents. In addition, relational capitals and relational governance mechanisms were identified to support the horizontal collaboration among these enterprises.Research limitations/implicationsThe focus is on only one part of the drinks industry, i.e. the brewery industry; therefore, this study could be extended to other industries within the drink sector or across manufacturing industries.Practical implicationsThe micro and small enterprises can collaborate to achieve relational rent, but this collaboration requires strong relational capitals, such as trust. These partners need to change informal governance mechanisms that already exist towards more contractual formal mechanisms.Originality/valuePrior research has largely focused on vertical collaboration, with limited studies using the relational theory lens to explicate horizontal collaboration phenomena and no previous research in the context of micro and small companies. Relational rents, relational capitals and relational governance mechanisms are studied to provide insights into an effective collaboration in this context.

COVID-19 is around the world. We attempt to apply three-step method in ISO/IEC Guide 51: 2014 to COVID-19 infection control in the workplace. The results show that the COVID-19 infection control measures include the eradication of the virus, the destruction of infectivity, the detoxification and weakening and the elimination of opportunities for infection as “Inherently Safe Design Measures”, the avoidance of contact as “Safeguarding and Complementary Protective Measures” and the reduction of contact and the avoidance of seriousness as “Information for Use”. Among these specific measures, the New Normal, especially in the manufacturing industries, would be “telecommuting” and “unmanned workplaces”, which are part of the elimination of opportunities for infection, and “changes in flow lines” and “changes in airflow”, which are part of the avoidance of contact. Where “telecommuting” and “unmanned workplaces” are feasible, they should be implemented as much as possible, and where they are not, attempts should be made to minimize human-to-human contact by “changes in flow lines”. In addition, in the area of “changes in airflow”, there are high expectations for future research on how to establish a ventilation design for COVID-19, in which but also the source would be workers themselves, not only combustible gases and toxic gases.

We test the Cohen & Klepper cost-spreading process share hypotheses using unique data from two national innovation surveys (2009 and 2012). To our knowledge, no other study has the same combination as our dataset, in terms of robust data from a mandatory survey, large sample size, diverse measures for innovation output, and no sample selection bias. We use two direct measures of innovation to test the CK hypothesis: R&D expenditure and the number of innovations. An outcome variable that counts the number of innovations can be easier for respondents to recall from memory and they may reflect the firm’s activities more accurately. Using direct measures of innovation eliminates three forms of bias emanating from patents. Our results show that the CK hypotheses can be supported with the aggregated sample, but the results are weak for separate industries. The count-based process share provides statistically superior results to the expenditure-based process share.

Background: Noise Induce Hearing Loss (NIHL) is a work accident which has a high incidence rate of workers ini the manufacturing industry nowadays. Attitudes and obedience behavior of manufacturing workers in using personal noise protective equipments are influenced by their knowledge about NIHL. Providing information such as health education periodically is needed to increase worker’s knowledge to change their attitudes and behaviors in order to obey safety regulations and using personal noise protective equipments. Objective: This study examines the effect of providing health counseling on the knowledge, attitudes, and behaviors of textile industry workers regarding noise induce hearing loss. Methods: This research method used quasi-experimental research method, with a one group pretest-posttest as design approach. Intervention of this research was a health counseling and the research instruments were leaflets, modules, and lectures about noise induced hearing loss. The subjects of this study were 35 workers of textile factories. Consecutive sampling were used to get subjects. Data on the level of knowledge, attitudes, and behavior were obtained through questionnaires before intervention and two weeks after the intervention was carried out. This research was located in one of the textile factories in Semarang Regency in 2020. Statistical analysis used Wilcoxon test, Fisher test, and Kolmogorov-Smirnov test. Results: The result of this research show that there was an increase in the mean score of subjects’s knowledge, attitudes and behavior. Statistical analysis show that that there is a significant differences between knowledge scores (p value = 0,000), attitudes scores (p value = 0,000), and behavior scores (p value = 0.024) before and after being given health education. Conclusion: The mean score of knowledge, attitudes and behavior of workers after being given information about noise induced hearing loss is higher than the average score of knowledge, attitudes and behavior of workers before being given a counseling.

Entrepreneurial leaders have the ability to influence business model innovation and entrepreneurial bricolage. Introducing alternative ideas and behaviors in an enterprise nowadays often linked to innovation. Companies are eager to take advantage of or benefit from new goods or services or technological marketing channels in this context. Due to the recognition of leadership as an important driver of business innovation, a perceptual framework has been established in order to study the consequences of entrepreneurial leadership on the desire to build business model innovation in organizations, with business acting as a mediating moderating function on entrepreneurial bricolage and entrepreneurial self-efficacy. To explore the conceptual model of the study, five hypotheses have been proposed. A self-managed survey was conceived to acquire cross-sectional responses from 325 people working in the Punjab, Pakistan manufacturing industry. The results demonstrated that, when entrepreneurial self-efficacy is high, the link between entrepreneurial leadership and business model innovation models is stronger. As a result, this is a one-of-a-kind cross-sectional study that investigates the mediating-moderating process of business bricolage and entrepreneurial self-efficacy in Pakistan's manufacturing industry. The study contributes to existing research while also assisting legislators in taking action to govern workplace self-efficacy and encouraging leaders to use entrepreneurial bricolage techniques and business model innovation.

Additive Manufacturing (AM) has a large potential to revolutionize the manufacturing industry, yet the printing parameters and part design have a profound impact on the robustness of the printing process as well as the resulting quality of the manufactured components. To control the printing process, a substantial number of parameters is measured while printing and used primarily to control and adjust the printing process in-situ. The question raised in this paper is how to benefit from these data being gathered to gain insight into the print process stability. The case study performed included the analysis of data gathered during printing 22 components. The analysis was performed with a widely used Random Forest Classifier. The study revealed that the data did contain some detectable patterns that can be used further in assessing the quality of the printed component, however, they were distinct enough so that in case the test and train sets were comprised of separate components the predictions’ result was very poor. The study gives a good understanding of what is necessary to do a meaningful analytics study of manufacturing data from a design perspective.

The purpose of this research is twofold: First, it aims to clarify the public subsidy effect on Small–Medium Enterprises’ (SMEs’) R&D expenditures by contrasting total R&D investments and net R&D investments excluding the amount of public funding. The second aim is to determine whether government subsidies induce firms to nonlinearly invest their own funds in R&D. To control for potential selection bias, we estimate the policy effect through matching techniques and a dose–response function with a generalized propensity score, using panel data that link the 2015 through 2019 waves of the South Korean Survey on the Technology of SMEs. We were not able to reject the hypothesis that uses a linear effect of public subsidies on SMEs’ R&D investments, suggesting a complementary effect on total R&D expenditures and a partial crowding-out effect for the net R&D case without a specific minimum threshold or a saturation point. Further investigation of a possible heterogeneous effect based on a subsample shows a U-shaped relationship, with a minimum threshold in the manufacturing industry. Our findings imply that public financial support for SMEs in South Korea has not completely prevented market failure beyond a certain level of public intervention. Importantly, the absolute amount of direct public support for individual SMEs should be increased in order to efficiently promote R&D spending in the manufacturing sector.

This study investigates whether an increase in wages of foreign firms generates the total factor of productivity (TFP) growth of Indonesian manufacturing firms by considering different job characte...

High-quality development of manufacturing industry is the key to leading the high-quality development of China's economy. The paper analyzes the mechanism and effect of the quality change of China's manufacturing industry enabled by digital economy. And then, it is considered that the basic pattern of China's manufacturing industry is that the manufacturing industry is large but not strong. As a result, quality change could focus on the intensive margin on the basis of strengthening and expanding the margin. However, the quality change of manufacturing industry enabled by digital economy is a complicated process. Therefore, the quality change of manufacturing industry would give full play to the decisive role of market mechanism while giving better play to the role of the government. The focus of policy could focus on incentives and synergy that are conducive to promoting the digital transformation of the manufacturing industry.

Under the influence of COVID-19, minor enterprises, especially the manufacturing industry, are facing greater financial pressure and the possibility of non-performing loans is increasing. It is very important for financial institutions to reduce financial risks while providing financial support for minor enterprises to promote industrial development and economic recovery. In order to understand the function of machine learning algorithms in predicting enterprise credit risk, the research designs five models, including Logistic Regression, Decision Tree, Naïve Bayesian, Support Vector Machine and Deep Neural Network, and adopts SMOTE and Undersampling to process imbalanced data. Experiments show that machine learning algorithms have high accuracy for both large-scale data and small-scale data.

China's overcapacities in manufacturing industries, including pollution-intensive industries, served as an important motivation of the Belt and Road Initiative (BRI). The popular Pollution Haven Hypothesis (PHH) therefore expects that the initiative will lead to the relocation of polluting industries from China to the recipients. Focusing on the implementation by local governments, we argue that actual outcomes of the BRI depend on the way local states and businesses respond to the BRI in accordance with their preferences. Through investigating industries’ actual responses to the BRI, we found that pollution-intensive industries have not relocated but rather expanded exports to the BRI countries. This has two implications: on the one hand, it alleviates the overcapacity issue in China and helps sustain the economic performance of the industry; on the other hand, it results in more pollution within Chinese borders and aggravates the environmental challenges facing the country.

The development of intelligent and data-driven product quality control system are emerging as key engineering technologies for industrial manufacturing process. And many studies have been made to investigate the application of quality control of industrial valve manufacturing process in cyber–physical systems (CPS). The purpose of this article is to provide a quality control and management system by using the modern electronics technology, information technology and network technology. Firstly, we propose an intelligent and data-driven framework model of product quality based on the advanced technology of digital twin (DT) and simulation methods for CPS. Secondly, we emphasize the manufacturing enterprise should hold a data accumulation, and give some useful advises on how to carry out a successful quality analysis system of industrial valve manufacturing process in CPS. Then, as a case, the intelligent method of BP neural network is constructed according to lots of quality characteristics (QCs) of the mechanical and electrical product of industrial valve, and the BP network is trained by using many quality failures of manufacturing process. Finally, the results show that the new quality control system has good accuracy and practicability by the practical example.

The government's environmental governance may be affected by corruption and affect the implementation of environmental policies. Unfortunately, existing research only considers environmental regulations (ER) and ignores the role of anti-corruption (AC) in green development. Using China's provincial manufacturing industry data from 1998 to 2017 as an example, this study investigated the impact of AC and ER on the green development of manufacturing (MGD). This study first determined the MGD by combining the epsilon-based measure model and the Malmquist-Luenberger index. Then, a spatial Dubin model was used to handle spatial effects and a panel threshold model was employed to investigate nonlinear effects. The results showed that: (i) AC and ER significantly improved MGD, and the spatial spillover effect of MGD was 0.467. (ii) ER and MGD have a non-linear relationship, when AC is at a low level, the implementation effect of ER is low, and as AC increases and exceeds the threshold 3.105, the implementation effect of ER increases significantly from 0.094 to 0.171. To make the results robust, this study implements a robustness test by replacing variables. Finally, the policy implies that the government should pay attention to the role of AC in improving MGD and consider the spatial spillover effect of AC, and promote the implementation effect of ER on MGD.

With unique datasets, this paper studies the distributional impact of high-speed rail (HSR) on industrial developments by examining the house price premium of industrial parks in two important core-periphery city pairs of China: Shanghai-Suzhou and Beijing-Langfang. We find that in core cities, the premium of service industrial parks (SIPs) has grown faster near HSR stations, while that of manufacturing industrial parks (MIPs) has grown slower near HSR stations. In periphery cities, however, the premium of SIPs has grown slower near HSR stations. Moreover, the premium of MIPs has grown faster near HSR stations of Suzhou. The results suggest that HSR facilitates a “spillover effect” between the core and peripheries for the manufacturing industry, but a “siphon effect” for the service industry. City-level GDP analysis for the two industries delivers consistent results. Our findings shed light on the underlying reason for the spatial variation in the economic impacts of HSR.

Sustainable manufacturing (SM) is crucial for our future manufacturing and it starts to have an evolutionary development. However, manufacturing industries are difficult to adopt sustainability measures because of considerable barriers under the triple bottom line (TBL): economy, environment and people. Previous research works mainly focused on the originality and the definitions of the barriers in SM, they seldomly consider the stakeholder-related affairs on SM and the causal relationships between the barriers in SM. Therefore, this study aims to propose a comprehensive analysis of barriers in SM using social network analysis (SNA), with detailed consideration of stakeholder concerns in terms of TBL. This study applies SNA to recognize and investigate the underlying stakeholder-related barriers and their causal relationships in SM, and the suggestions were provided upon the findings of SNA to help for mitigating the negative influences from critical barriers to SM. The validation is provided by showing the effectiveness of suggestions in which decreases in the network density and average geodesic distance simultaneously after the modification. This study contributes to not only displaying the efficient way to probe the stakeholder-related barriers in SM, but also offering the guideline to support the measures proposing in the future by using the same analytic technique in SNA which is demonstrated in this study.

The phenomenon that there are still many manufacturing industry companies on the Indonesia Stock Exchange that have a PBV smaller than one is the main basis for conducting the study. This study aims to analyze the effect of financial policy and financial performance on firm value. The sampling technique was based on purposive sampling. The data analysis technique used a linear regression model. Based on the analysis and discussion results, there are four main findings obtained from this study: First, the model used is significant to explain changes in firm value with the ability to explain 48.7 percent. Second, of the five independent variables, there are three variables: the policy in working capital management and the performance variable, namely the volatility of expectations and returns, which have a significant effect. To the value of the company. Third, the company's financial performance factors have a more dominant influence on the company's value dynamics than policy factors. Fourth, the direction coefficient of the influence of the independent variable on the dependent variable, although the two variables are not significant. The practical implication is to increase the value of a manufacturing company. Therefore, it is advisable to consider financial policies and financial performance. Theoretically, financial management based on signal theory and trade-off theory of Islamic perspective theory can increase firm value.

Due to current trends in the manufacturing industry, such as mass customization, manual operations contribute drastically to the overall costs of a product. Methods-Time-Measurement (MTM) identifies the optimization potential of manual workplaces, which significantly influences a worker's productivity. However, traditional MTM requires great efforts to observe and transcribe manual assembly processes. Yet, various digital approaches exist that facilitate MTM analyses. While most of these approaches require the existence of real workplaces or cardboard mock-ups, it would be beneficial to conduct a virtual MTM in earlier phases of production planning. However, the quality of virtual MTM analyses compared to traditional MTM conducted in reality has not been assessed yet. This paper is addressing it by conducting a comparative user study with 21 participants completing the same task both at a real and virtual workplace, which they access via Virtual Reality technology. Our results show that participants' MTM-2 values achieved at the VR workplace are comparable to the real workplace. However, time study data reveals that participants moved considerably slower in VR and thus needed more time to accomplish the task. Consequently, for the measurement of manual work in VR it is even necessary to utilize predetermined times, such as MTM-2 since time study data is insufficient. This paper also serves as a proof of concept for future studies, investigating automated transcription systems that would further decrease the efforts conducting MTM analyses., The International Journal of Advanced Manufacturing Technology, 117, ISSN:0268-3768, ISSN:1433-3015

The trade policy pursued by the US government certainly provides as one of the most important measures to stimulate the export of those commodity groups that determine the development of the country's economy, shape its innovative nature and the possibilities for the expansionist promotion of American capital in the global, global geo-economic space. Such goods include high tech products of the American manufacturing industry, the forms, means, tools and methods of export promotion of which are the subject of this study. Having studied the evolutionary dynamics of the volume and structure of the stimulating elements of export regulation of American high-tech products for the period 1946–2019, we identified long-term trends characterizing the effective combination of assistance, encouragement, assistance and support to national exporters of the relevant commodity groups in the foreign trade activities of the United States. Based on the results of the study, conclusions are drawn about the unconditional priority of stimulating the export of high-tech products of the US manufacturing industry during the entire period under consideration, characterized by a flexible combination of the use of appropriate forms, means, tools and methods of this stimulation. The author emphasizes the primacy of expediency and efficiency in the choice of directions for the expansionary promotion of high-tech products of the American economy to the foreign market, which, of course, is of practical interest for Russian use.