Small Manufacturing Research Articles

The Impacts of Cyberattack on SMEs in the USA and Way to Accelerate Cybersecurity

We are at the 4th industrial revolution called industry 4.0. The world is turning from digitalization to automation. Technological advancement and adoption and utilization of changing pattern of technology is gaining the gear at all social, political, diplomatic, economic and commercial spheres including SMEs. Technological advancement is bringing speed, innovation and sophistication of products and services in SMEs in one hand and on the other hand, cyber hacking and various and changing pattern of cybercrimes are hampering the growth and development. The aim of the study is to analysis the impacts of cyberattacks on SME’s productivity, growth and development in USA and potential way to accelerate the cyber security in the area. The study is mainly based on secondary sources of data including journals, research publications, scholarly articles, thesis papers etc. The finding of the study revealed that Banking and finance, healthcare, small manufacturing firms, retailers and E-commerce, public transport and infrastructure with less than 500 employees are the most vulnerable sectors for the Cyber-attack in the USA. The most commonly practiced cyberattacks are Phishing attacks, Ransomware, Malware, DDoS attacks, MitM etc. The Study suggests a number of cyber security measures including employee awareness and training program, creation of security policy and practice, know how to distinguish between fake antivirus offer and real notification and protect OT-IT system to prevent the damage.

Effect of Preheating Parameters on Extrusion Welding of High-Density Polyethylene Materials.

High-density polyethylene (HDPE) has emerged as a promising alternative to fiber-reinforced plastic (FRP) for small vessel manufacturing due to its durability, chemical resistance, lightweight properties, and recyclability. However, while thermoplastic polymers like HDPE have been extensively used in gas and water pipelines, their application in large, complex marine structures remains underexplored, particularly in terms of joining methods. Existing techniques, such as ultrasonic welding, laser welding, and friction stir welding, are unsuitable for large-scale HDPE components, where extrusion welding is more viable. This study focuses on evaluating the impact of key process parameters, such as the preheating temperature, hot air movement speed, and nozzle distance, on the welding performance of HDPE. By analyzing the influence of these variables on heat distribution during the extrusion welding process, we aim to conduct basic research to derive optimal conditions for achieving strong and reliable joints. The results highlight the critical importance of a uniform temperature distribution in preventing defects such as excessive melting or thermal degradation, which could compromise weld integrity. This research provides valuable insights into improving HDPE joining techniques, contributing to its broader adoption in the marine and manufacturing industries.

Entrepreneurial ecosystem—Industrial parks as catalysts for strengthening ventures’ capability: Evidence from Ethiopian small manufacturing enterprises

Entrepreneurial ecosystem—Industrial parks as catalysts for strengthening ventures’ capability: Evidence from Ethiopian small manufacturing enterprises

Deep learning-based anomaly detection using one-dimensional convolutional neural networks (1D CNN) in machine centers (MCT) and computer numerical control (CNC) machines

Computer numerical control (CNC) and machine center (MCT) machines are mechanical devices that manipulate different tools using computer programming as inputs. Predicting failures in CNC and MCT machines before their actual failure time is crucial to reduce maintenance costs and increase productivity. This study is centered around a novel deep learning-based model using a 1D convolutional neural network (CNN) for early fault detection in MCT machines. We collected sensor-based data from CNC/MCT machines and applied various preprocessing techniques to prepare the dataset. Our experimental results demonstrate that the 1D-CNN model achieves a higher accuracy of 91.57% compared to traditional machine learning classifiers and other deep learning models, including Random Forest (RF) at 89.71%, multi-layer perceptron (MLP) at 87.45%, XGBoost at 89.67%, logistic regression (LR) at 75.93%, support vector machine (SVM) at 75.96%, K-nearest neighbors (KNN) at 82.93%, decision tree at 88.36%, naïve Bayes at 68.31%, long short-term memory (LSTM) at 90.80%, and a hybrid 1D CNN + LSTM model at 88.51%. Moreover, our proposed 1D CNN model outperformed all other mentioned models in precision, recall, and F-1 scores, with 91.87%, 91.57%, and 91.63%, respectively. These findings highlight the efficacy of the 1D CNN model in providing optimal performance with an MCT machine’s dataset, making it particularly suitable for small manufacturing companies seeking to automate early fault detection and classification in CNC and MCT machines. This approach enhances productivity and aids in proactive maintenance and safety measures, demonstrating its potential to revolutionize the manufacturing industry.

Impact of the Formality Level on the Strategic Planning Process of SMEs

The article identifies the barriers that hinder the implementation of strategic planning and the relationship with the level of formality in the preparation of strategic plans of SMEs in Quito. It focuses on the manufacturing sector and its different sub-sectors, including the manufacture of food products, textiles, clothing, as well as chemical, pharmaceutical, medicinal, and botanical substances for pharmaceutical use, in addition to rubber and plastic products. The existing literature reviewed on strategic planning and tools to address the process characterizes the small and medium-sized manufacturing sector as the object of research. The subsequent field study shows the results achieved by the companies with planning and the existence or not of barriers to strategic implementation. The most common barriers have been identified in relation to factors such as resources, culture, lack of technological support, among others. Once the barriers have been identified, they are linked to the use of planning tools to determine the type of existing relationship. There is a moderate correlation between the level of complexity and the level of execution of the strategic plan. The research results will enable further research on the importance of the use of management tools in SMEs.

Identification and Analysis of Key Factors Affecting Digital Transformation of Small and Medium-Sized Manufacturing Enterprises

The digital transformation of small and medium-sized manufacturing enterprises is influenced by various factors, and the relationship between them is not yet clear. Studying the factors that affect the digital transformation of small and medium-sized enterprises can promote the digital transformation process of small and medium-sized manufacturing enterprises. On the basis of summarizing literature and expert recommendations, this study identified the influencing factors in the digital transformation process of small and medium-sized manufacturing enterprises, and analyzed the key influencing factors using a combined method of DEMATEL-ISM-MICMAC (Decision-Making Test and Evaluation Laboratory-Interpretive Structural Model-Matrices Impacts Croises-Multiplication Appliance Classement). Research has found that digital policies, market demand, business model innovation, third-party data-driven services, and the digital foundation of enterprises are key factors in the process of digital transformation. In addition, the causal factors in the DEMATEL method, the essential factors in the ISM method analysis, and the independent factors in the MICMAC technique analysis can mutually support and complement each other. This study enriches the methodology for studying the factors of digital transformation and provides reference for the digital transformation of small and medium-sized manufacturing enterprises and government policy formulation.

Achieving supply chain sustainability: enhancing supply chain resilience, organizational performance, innovation and information sharing: empirical evidence from Chinese SMEs

PurposeThis study aimed to explore the relationship between supply chain resilience (SCR) and organizational performance (OP), with innovation (INN) serving as a mediator and information sharing (IS) acting as a moderator.Design/methodology/approachThe study comprehensively examined the connections between SCR, OP, INN and IS. An exploratory approach and quantitative methods were employed. The data were collected from small and medium-sized manufacturing enterprises of three cities Xian, Hainan and Guangzhou of China via online questionnaire surveys conducted through Emails and WeChat. SmartPLS-4 was used for data analysis.FindingsThe findings indicated that SCR has a positive effect on sustainability efforts. Additionally, INN and effective IS both mediated and moderated this relationship, playing crucial roles in improving sustainability within the supply chain.Practical implicationsThe study offered practical insights for businesses to enhance their sustainability efforts. Managers can use these findings to develop strategies that improve SCR, foster INN and encourage effective IS, ultimately resulting in a more sustainable supply chain.Originality/valueThis study enriched the existing knowledge base by investigating the intricate relationships among SCR, OP, INN and IS, all within the context of achieving sustainability. By exploring these elements holistically, the research introduced originality and highlighted effective strategies for sustainable supply chain management.

Enhancing industrial IoT with edge computing and computer vision: An analog gauge visual digitization approach

The advent of Industry 4.0 has led to the widespread adoption of Industrial Internet of Things (IIoT) and Computer Vision technologies in manufacturing. However, handling the massive data generated by IIoT poses challenges. To address this, we propose a software and hardware architecture that combines edge computing with IIoT to enable computer vision applications on manufacturing floors. This research contributes to integrating edge computing and IIoT with Computer Vision technologies in manufacturing facilities, offering a cost-effective and scalable solution for machine vision applications. This approach benefits Small and Medium Manufacturers (SMMs) by utilizing low-cost hardware and open-source technologies, enabling them to harness Industry 4.0 advantages. Our approach involves IoT devices using Raspberry Pi microcomputers and USB webcams as clients and a Python-based edge node server software as the central component. Our test case study results show that a centralized edge-computing solution can offer several useability benefits and a significant performance increase over using a non-edge-enabled IIoT approach. The proposed architecture is tested, validated, and verified through a case study focused on the digitization of the readings of analog gauges. Our experimentation results can offer valuable insights and guidance for the broader adoption of edge-enabled IIoT solutions in manufacturing contexts.

Pickup and Delivery Vehicle Routing Problem with Hybrid Missions and Third-Party Vehicle Rentals: A Case Study of Animal Feed Industry

The vehicle routing problem for small and medium-sized animal feed manufacturers is a complex challenge because each transport route can vary significantly between delivering products to customers and picking up raw materials to return to the factory. Currently, businesses lack well-planned management for utilizing a limited number of trucks. As a result, they often incur additional costs by relying on third-party vehicle rentals. This research aims to reduce transportation costs for small and medium-sized animal feed manufacturers by solving a formulated mixed-integer linear programming (MILP) model, using experimental data that accurately reflects the actual problems faced. The MILP model results help reduce transportation costs by up to 18.5% compared to current practices by optimizing route sequences and incorporating the use of third-party vehicle rentals. This also serves as a guideline for reducing transportation costs in other similar industries.

Enhancing MSMEs Financial Resilience: Integrating Working Capital Management and Sustainability Reporting

This study examines the influence of sustainability reporting (SR) comprehension and working capital management (WCM) on the financial performance of small and medium-sized manufacturing enterprises (MSMEs). Furthermore, the study emphasizes WCM's impact on financial performance, which is linked to understanding SR among MSMEs actors. The study incorporates control variables in the model (e.g., age, size, ownership type, organizational culture, market orientation, entrepreneurial orientation). The sample is selected using quota sampling of MSMEs in the manufacturing sector in Palembang, Indonesia, from October to November 2023. Primary data collection is distributed online through questionnaires. The results show that understanding SR and WCM positively affect the financial performance of MSMEs. The findings deliver several contributions. Firstly, the implementation of SR of MSMEs – in the long term – would benefit the government in supporting sustainable development goals (SDGs). Secondly, it bridges the literature gap regarding the implementation of SR and WCM to examine the performance of MSMEs.

Understanding Knowledge and Health Behaviors Regarding Noise Prevention Practices Among Workers in a Small Automotive Parts Manufacturer in Chonburi Province

Understanding Knowledge and Health Behaviors Regarding Noise Prevention Practices Among Workers in a Small Automotive Parts Manufacturer in Chonburi Province

Will Network Infrastructure Optimization Make Manufacturing Enterprises "Out of Real to Virtual"? --- A Quasi-Natural Experiment from the "Broadband China" Policy

Manufacturing is the most important component of the real economy, and the application of modern network information technology can effectively improve the operational efficiency of manufacturing enterprises. In the context of "Made in China 2025", it is particularly important to prevent manufacturing enterprises from deviating from their main business and becoming excessively financialized. Maintaining the essential business activities of manufacturing enterprises is of great importance to China's economic development. Based on the operating data of all A-share listed manufacturing companies from 2010 to 2020 and combining the "Broadband China" demonstration city policy, this paper uses a multi-point double-differenced model to explore the relationship between network infrastructure optimization and excessive financialization of manufacturing enterprises. The research shows that: 1) Network infrastructure optimization will make manufacturing enterprises increase their financialization level, and this effect is mainly manifested through optimizing accounts receivable management. 2) From the perspective of enterprise size, compared with small and medium-sized manufacturing enterprises, large manufacturing enterprises are more likely to improve their financialization level through network infrastructure optimization. 3) From the perspective of the degree of diversified operations, manufacturing enterprises with high diversified operations are more likely to take advantage of network infrastructure to improve their financialization level. This study provides reference and guidance for later researchers on the impact of "new infrastructure" represented by network infrastructure construction on the business model of manufacturing enterprises.

Physicochemical and sensory evaluation of the quality of crude palm oil (Elaeis guineensis) produced artisanally and industrially in Brazil

Palm oil is primarily used in the crude form in northeastern Brazil's cuisine. Most of its production is carried out by small manufacturers, who use the profits from sales as a subsidy to supplement their family income. Evaluating the physicochemical and sensory quality of palm oil is essential to help producers develop higher-quality artisanal products. This study aimed to analyze samples of crude palm oil produced and sold in the city of Taperoá (BA) and other industrialized brands sold in Salvador (BA). Seven palm oil samples underwent physicochemical analysis (acidity, carotenoid content, instrumental color, iodine value, peroxide value, Kreis reaction, saponification value) and sensory analysis (acceptance and ranking tests). Our findings revealed significant variation in the evaluated parameters, with most samples showing inadequate results for the regulatory parameters of acidity and iodine values, as well as unsatisfactory results for carotenoids and the Kreis reaction across all samples. Variations in color analysis were likely associated with differences in carotenoid content among the samples. The acceptance tests showed that most samples scored above average for all evaluated characteristics, except for the industrial sample from Taperoá (sample 06), which showed the lowest averages for color (4.5), odor (5.2), viscosity (3.2), and overall impression (4.3). In the ranking test, sample 02 from artisanal production (Taperoá-BA) was the most preferred in all categories, while sample 06 from industrial production (Nazaré-BA) was the least preferred in all categories. These results indicate opportunities for improving both traditional and industrial crude palm oil production methods, which could lead to an increase in income for the population that depends on this product.

Stakeholders’ Perceptions on Influence of Energy Efficiency Practices Adopted on Economic Performance of Selected Small and Medium Sized Manufacturing Enterprises in Nakuru County, Kenya

The adoption of environmental policy among large manufacturing firms has been recognized for enhancing their economic performance. This is crucial for achieving Kenya's Vision 2030, the fourth medium term plan (2023-2027) and the Bottom-Up Economic Transformation Agenda (BETA) for Inclusive Growth. Despite the slow pace, small and medium-sized enterprises (SMEs) are now adopting these policies to reduce their environmental footprint. However, there is limited documentation on how these practices affect their economic performance. Hence, this study aimed at examining stakeholders' perceptions on the influence of adopting energy efficiency practices on the economic performance of selected manufacturing SMEs in Nakuru County. The study was guided by the ecological modernization theory (Win-Win principle). An explanatory sequential mixed-method research design was employed, targeting SME proprietors in the manufacturing sector with a sample size of 76 respondents. Descriptive and inferential statistics (linear regression) was used to analyze quantitative data, while content analysis was used to analyze qualitative data. The study found out that SMEs largely adopted the use of energy-efficient bulbs and turned off lights when not in use. However, they used solar lighting as an energy efficiency practice to a lesser extent because they consider this practice expensive. The study also found that stakeholders perceived that energy efficiency practices adopted had a significant influence on the economic performance of selected manufacturing SMEs. This finding implied that energy efficiency practices adopted by manufacturing SMEs would have an influence on SMEs economic performance. This study recommends that the government, both national and county should sensitize the SMEs as well as allocate financial and technical resources to support SMEs implement and upscale their energy efficiency practices within their operations. The focus of energy efficiency practices should be on those that reduce production costs and enhance competitiveness such as those that improve SMEs customer base

Time management as the growth factor of small manufacturing enterprises

The article deals with small manufacturing enterprises as a point of an industry economic growth which potentially outpaces the average growth rate of the industry and the GDP growth rate that makes it possible to increase the share of gross production product in the general structure of small business of Russia. As one of the reserves of growth of such enterprises the author presents implementation of corporate time management technologies which allow the administration of the enterprises to increase the time for solving the tasks facilitating the economic growth: working with the major clients and contracts, searching for new financial sources, introduction of new capacities, development of new products, formation and development of new management teams. The author suggests the structure of a corporate time management standard which regulates the issues of managing meetings, calendars, operational tasks, work communications. The article contains description of the method of implementation of corporate time management at the example of a small manufacturing enterprise of the instrumentation industry.

The impact of competitive strategy on enterprise performance: An empirical study of small and medium-sized manufacturing enterprises

This study investigates the relationships between competitive strategy, innovation, corporate governance structure, capital structure, human capital, and enterprise performance in small and medium-sized manufacturing enterprises (SMEs). The research is based on the Competition Theory. The survey research design includes 506 valid responses from SMEs in China. Structural equation modelling was employed to analyze the responses. It revealed that competitive strategy positively impacts performance, with innovation and human capital as key mediators. Corporate governance and capital structure also mediate these relationships, supporting various strategic management theories. Additionally, the environment moderates the impact of competitive strategy on performance, highlighting the need for adaptability in dynamic markets. These findings offer theoretical substantiations and practical insights for enhancing SME performance through strategic planning. Future research should employ longitudinal approaches and integrate objective data to explore these dynamics further.

중소 수출 제조기업의 빅데이터 분석 역량이 공급망 회복탄력성과 공급망 성과에 미치는 영향에 관한 연구 - 기계/장비 산업을 중심으로

As the economic environment of the global market is rapidly changing, uncertainty is increasing, and technological innovation, as well as financial and human resources, are becoming important factors. In particular, small and medium-sized export manufacturing companies are building global supply chains to improve their competitive advantage, and big data analytics capabilities to collect and analyze manufacturing and import/export information have been raised as a way to solve these risks. Therefore, this study analyzed the influence of big data analytics capabilities on supply chain performance through logistics flexibility and supply chain resilience in the supply chain formation of small and medium-sized export manufacturing firms. The survey was distributed to small and medium-sized export manufacturing companies from January 3, 2024, to March 31, 2024, through face-to-face, email, mail, and fax, focusing on the list of member companies provided by the Korea International Trade Association, the Ministry of SMEs and Startups, the Smart Manufacturing Innovation Association, and the SME Technology Information Promotion Agency. More than 2,000 copies were distributed and 215 copies (21.5%) were collected, and 203 copies of the questionnaire were constructed after removing 12 non-response questionnaires. Based on the collected questionnaires, the analysis was conducted using SPSS Ver. 28.0 and the extension program Process Macro Ver. 4.2. The results of the empirical analysis of this study are as follows. First, big data analytics capabilities have a positive impact on supply chain performance. Second. big data analytics capabilities have a positive effect on supply chain performance through the mediation of logistics flexibility. Third, big data analytics capabilities have a positive effect on supply chain performance through the mediation of supply chain resilience. Fourth, big data analytics capabilities have a positive effect on supply chain performance through the dual media.

Navigating the Fourth Industrial Revolution: SBRI - A Comprehensive Digital Maturity Assessment Tool and Road to Industry 4.0 for Small Manufacturing Enterprises

Navigating the Fourth Industrial Revolution: SBRI - A Comprehensive Digital Maturity Assessment Tool and Road to Industry 4.0 for Small Manufacturing Enterprises

Educating Engineers on the Use of Renewable Ethanol Fuel as a Drop-in Replacement for Gasoline in Small Engines

The use of high-blend ethanol fuels to reduce emissions produced by on-road vehicles has been extensively studied. However, much less research has been done to study the effect of operating small off-road engines on high-blend ethanol fuel as a drop-in replacement for gasoline. Most small engine manufacturers only certify proper operation on low ethanol blends such as E10 (10% ethanol, 90% gasoline by volume). Most engineering students are unaware of the benefits that can be achieved when using high-blend ethanol fuel in small engines without substantial modifications. In this study, students conducted performance testing and analysis of a small engine using a dynamometer and a raw exhaust emissions analyser. The exhaust emissions and performance of the engine were evaluated using the U. S. Environmental Protection Agency (EPA) 6-mode duty cycle for small recreational engines (under 19 kW). Testing and analysis followed the recommendations of the SAE J1088 recommended practice. Students were motivated by the contemporary nature of the project and the use of commercially available equipment for testing. Further, students learned about the use of standardized testing to demonstrate the performance and emissions results.

The impact of buying external technology on employment and air quality: an empirical approach in Vietnamese manufacturing SMEs

Purpose The purpose of this paper is to evaluate the current situation of buying external technology in Vietnamese manufacturing small and medium enterprises (SMEs) from 2013 to 2018. This paper also aims to examine the effect of buying technology on employment and environmental quality in Vietnam. Design/methodology/approach External technology purchase and its impact on employment and environmental quality are taken from the Vietnam annual enterprise survey and the using technology in production survey from 2013 to 2018. The estimation is based on a feasible generalized least squares method. Findings This study finds that external technology purchase in manufacturing SMEs increases the employment rate in the industries. External technology purchase in Vietnamese manufacturing SMEs also increases the level of environmental pollution. This is a negative side of purchasing technology for production because if the technology used is old, outdated and of poor quality, it will increase environmental pollution. In addition, the growth in employment increases air pollution. This shows that purchasing advanced technology selectively helps to increase the employment rate in Vietnamese manufacturing sector, which is followed by a positive impact on environmental quality. Research limitations/implications The limitation of this study is that the research period was only investigated from 2013 to 2018 because the General Statistics Office of Vietnam no longer surveys the dataset about using technology in production surveys after 2018. This study has been conducted at the firm level, so results cannot be easily extended to the macroeconomic level, also taking into account the data limitations in terms of sector coverage. Practical implications This paper provides necessary policy recommendations for the government and manufacturing SMEs to solve negative technology issues related to the labour market and air quality in Vietnam. The results are expected to help policymakers in Vietnam propose appropriate national science and technology programmes towards sustainable development in the coming decades. Originality/value This paper focuses on assessing the effects of buying external technology by Vietnamese small and medium-sized manufacturing enterprises on employment and air quality.