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The purpose of this study is to explore the relationship between Lean manufacturing and Industry 4.0 for small and medium size of enterprise in Japan and Brazil.

The authors conducted a quantitative survey (20 companies in Japan and 30 companies in Brazil) combined with a qualitative interview (2 companies in Japan and 15 companies in Brazil).

According to the quantitative study, 90% of them practice Lean manufacturing and 40% of them practice Industry 4.0. In the qualitative study in Brazil, four managers responded that the Lean manufacturing is a prerequisite for Industry 4.0 since any production process with waste cannot be productive, even with sophisticated digitalization technology.

The authors explored further the relationship between “defensive Digital Transformation (DX),” which is based mainly on Lean manufacturing, and “offensive DX,” which relates to customer value creation through Industry 4.0. This study clarifies the relationship and plays as a roadmap to develop better the manufacturing from current status to the vision of Industry 4.0.

This paper aims to overcome the inability of both comparing loss costs and accounting for production resource losses of Overall Equipment Effectiveness (OEE)-related approaches.

The authors conducted a literature review about the studies focusing on approaches combining OEE with monetary units and/or resource issues. The authors developed an approach based on Overall Equipment Cost Loss (OECL), introducing a component for the production resource consumption of a machine. A real case study about a smart multicenter three-spindle machine is used to test the applicability of the approach.

The paper proposes Resource Overall Equipment Cost Loss (ROECL), i.e. a new KPI expressed in monetary units that represents the total cost of losses (including production resource ones) caused by inefficiencies and deviations of the machine or equipment from its optimal operating status occurring over a specific time period. ROECL enables to quantify the variation of the product cost occurring when a machine or equipment changes its health status and to determine the actual product cost for a given production order. In the analysed case study, the most critical production orders showed an actual production cost about 60% higher than the minimal cost possible under the most efficient operating conditions.

The proposed approach may support both production and cost accounting managers during the identification of areas requiring attention and representing opportunities for improvement in terms of availability, performance, quality, and resource losses.

This research aims to enhance understanding of the safety climate within small and medium-sized construction enterprises (SMEs). By conducting an in-depth analysis of safety practices and management approaches in this sector, it identifies critical gaps and provides actionable recommendations to improve the safety climate in construction SMEs.

An integrated method approach was employed, integrating quantitative and qualitative elements. A fishbone diagram model was developed to categorize key safety factors into four categories: Workers, Equipment, Management and Environment. Based on these categories, core safety parameters for SMEs were derived. A 42-question survey was developed and distributed to foremen across various construction sites in Eilat, Israel, aiming to capture diverse safety practices and illuminate the specific safety practices within these SMEs.

Key findings underscore variability in safety management practices across different sites, emphasizing management’s role and the prioritization of equipment and environment in safety protocols. The study revealed a strong correlation between higher safety scores and reduced accident rates, highlighting the efficacy of robust safety management. The research also correlates financial investment in safety with improved outcomes yet stresses the importance of strategic resource deployment, particularly in settings with limited resources. Additionally, inconsistencies in near-miss reporting were identified, suggesting the need for standardization to leverage these incidents for safety enhancement.

The research has certain limitations, including its narrow geographical focus on the city of Eilat, situated in a southern and arid region that presents specific climate challenges. Another limitation is the relatively small sample size, consisting of 20 sites. However, it is important to note that the significance of the findings has been rigorously assessed using test statistics, which have yielded satisfactory levels of significance.

The research establishes a practical framework for the development, management and maintenance of a safety climate in construction SMEs. Clear leading indicators are defined, enabling construction SMEs to cultivate a sustainable safety climate, enhance safety measures and prevent work accidents.

The research presents a comprehensive theoretical and practical framework for establishing, managing and controlling the safety climate in construction SMEs. It introduces leading indicators as effective tools for enhancing the safety climate in SMEs, offering a robust framework for cultivating a sustainable safety environment at both the site and company levels.

This study provides valuable insights into the safety climate of construction SMEs, offering a foundation for targeted improvements and informing future research directions in construction safety management. This analysis highlights SMEs' unique challenges and practices, providing valuable perspectives for enhancing safety in this critical construction industry sector.

Utilizing electrical discharge machining (EDM) to process micro-holes in superalloys may lead to the formation of remelting layers and micro-cracks on the machined surface. This work proposes a method of composite processing of EDM and ultrasonic vibration drilling for machining precision micro-holes in complex positions of superalloys.

A six-axis computer numerical control (CNC) machine tool was developed, whose software control system adopted a real-time control architecture that integrates electrical discharge and ultrasonic vibration drilling. Among them, the CNC system software was developed based on Windows + RTX architecture, which could process the real-time processing state received by the hardware terminal and adjust the processing state. Based on the SoC (System on Chip) technology, an architecture for a pulse generator was developed. The circuit of the pulse generator was designed and implemented. Additionally, a composite mechanical system was engineered for both drilling and EDM. Two sets of control boards were designed for the hardware terminal. One set was the EDM discharge control board, which detected the discharge state and provided the pulse waveform for turning on the transistor. The other was a relay control card based on STM32, which could meet the switch between EDM and ultrasonic vibration, and used the Modbus protocol to communicate with the machining control software.

The mechanical structure of the designed composite machine tool can effectively avoid interference between the EDM spindle and the drilling spindle. The removal rate of the remelting layer on 1.5 mm single crystal superalloys after composite processing can reach over 90%. The average processing time per millimeter was 55 s, and the measured inner surface roughness of the hole was less than 1.6 µm, which realized the  micro-hole machining without remelting layer, heat affected zone and micro-cracks in the single crystal superalloy.

The test results proved that the key techniques developed in this paper were suite for micro-hole machining of special materials.

The implementation of the digital economy has had a considerable influence on the manufacturing industry, and this paper aims to address the important issues of how to capture the opportunities presented by digital innovation and promote the transformation and upgrading of the manufacturing industry, as well as the improvement of quality and efficiency.

Using panel data from 30 Chinese provinces and cities between 2010 and 2021, this study establishes the panel vector autoregression (PVAR) model and uses impulse response function analysis to evaluate the influence of the digital economy on the high-quality transformation and upgrading of China's small home appliance industry across five dimensions under the digital economy.

The development of digital infrastructure has not demonstrated a noteworthy capacity for advancing the transformation and upgrading of the small home appliance industry. Furthermore, digital industrialization has exerted a minimal restraining influence on this process. Nevertheless, digital governance has consistently exhibited a substantial impact on facilitating the transformation and upgrading of the small home appliance industry. While both industrial digitization and digital innovation hold significant potential for promoting the transformation and upgrading of the small home appliance industry, their sustainability remains limited.

The organization should logically join independent innovation and open innovation, construct an industrial ecosystem for the profound convergence of the digital economy and compact household appliances, use digital-wise science and technology to empower the establishment of brand effects, strengthen the portrayal of the digital standard framework for the intelligent compact household appliance industry, advance the development of a public stage for computerized administrations in the compact household appliance industry and develop a strategy ecosystem for computerized assets in the compact household appliance industry.

This study offers systematic evidence of the relationship between the digital economy and the development of the small home appliance industry. The results of this research contribute to the literature on the impact of the digital economy on the manufacturing sector and provide a logical explanation for the transformation and upgrading of the small home appliance industry within the context of the digital economy.

Visual feedback control is a promising solution for robots work in unstructured environments, and this is accomplished by estimation of the time derivative relationship between the image features and the robot moving. While some of the drawbacks associated with most visual servoing (VS) approaches include the vision–motor mapping computation and the robots’ dynamic performance, the problem of designing optimal and more effective VS systems still remains challenging. Thus, the purpose of this paper is to propose and evaluate the VS method for robots in an unstructured environment.

This paper presents a new model-free VS control of a robotic manipulator, for which an adaptive estimator aid by network learning is proposed using online estimation of the vision–motor mapping relationship in an environment without the knowledge of statistical noise. Based on the adaptive estimator, a model-free VS schema was constructed by introducing an active disturbance rejection control (ADRC). In our schema, the VS system was designed independently of the robot kinematic model.

The various simulations and experiments were conducted to verify the proposed approach by using an eye-in-hand robot manipulator without calibration and vision depth information, which can improve the autonomous maneuverability of the robot and also allow the robot to adapt its motion according to the image feature changes in real time. In the current method, the image feature trajectory was stable in the camera field range, and the robot’s end motion trajectory did not exhibit shock retreat. The results showed that the steady-state errors of image features was within 19.74 pixels, the robot positioning was stable within 1.53 mm and 0.0373 rad and the convergence rate of the control system was less than 7.21 s in real grasping tasks.

Compared with traditional Kalman filtering for image-based VS and position-based VS methods, this paper adopts the model-free VS method based on the adaptive mapping estimator combination with the ADRC controller, which is effective for improving the dynamic performance of robot systems. The proposed model-free VS schema is suitable for robots’ grasping manipulation in unstructured environments.

Mental health problems are a grave concern in construction. Although the distinction between high job demands and low job resources, as reflected in the Job Demands-Resources (JD–R) model, has been used to examine the extent to which psychosocial hazards influence mental health for construction practitioners, limited research has reflected on the nature of these psychosocial hazards by exploring experiences of site-based construction practitioners.

This study adopted a phenomenological approach to examine people’ experiences and thoughts of the complex phenomena of psychosocial hazards and mental health in construction. In total, 33 semi-structured interviews were undertaken with site-based construction practitioners in Australia to unveil construction-focused psychosocial hazards and their effects on mental health. The data were analysed via content analysis, employing an interpretation-focused coding strategy to code text and an individual-based sorting strategy to cluster codes.

Eighteen psychosocial hazards were identified based on the JD–R model. Six of these represented a new contribution, describing salient characteristics inherent to the construction context (i.e. safety concerns, exposure to traumatic events, job insecurity, task interdependency, client demand and contract pressure). Of particular importance, a number of interrelationships among psychosocial hazards emerged.

The significance of this qualitative research lies in elucidating psychosocial hazards and their complex interrelatedness in the context of the mental health of construction practitioners, enriching the understanding of this central health and safety issue in the high-risk setting of construction work. The findings contribute to addressing mental health issues in the Australian construction industry by identifying higher order control measures, thereby creating a mentally healthy workplace.

Sustainable development is inseparable from rational and responsible use of resources and promotion of green entrepreneurship. The contemporary green development agenda encompasses climate, economic, technical, social, cultural, and political dimensions. International efforts to greening the global development are conducted by the major economies, including China as the world’s largest consumer of energy and the biggest emitter of greenhouse gases. China is aware of its environmental problems, as well as of its part of the overall responsibility for the accomplishment of the sustainable development goals. By means of the decarbonization efforts, the latter are integrated both into the national development agenda (the concept of ecological civilization) and China’s international initiatives (the greening narrative within the Belt and Road Initiative). Over the past decade, China has made a breakthrough on the way to promoting green entrepreneurship and greening of its development (better quality of air and water, renewable energy, electric vehicles, and organic farming). On the other hand, emissions remain high, agricultural land loses productivity, and freshwater resources degrade due to climate change. In conventional industries (oil, coal mining, and electric and thermal energy), decarbonization faces an array of impediments. In this chapter, the authors summarize fundamental provisions of China’s approach to building an ecological civilization and measures to reduce emissions and achieve the carbon neutrality status within the nearest decades. The analysis of obstacles to the decarbonization of the economy and possible prospects for the development of green entrepreneurship summarizes China’s practices for possible use in other countries.

The purpose of this study is to present the systematic literature review (SLR) on Lean Six Sigma (LSS) by exploring the state of the art on growth of literature on LSS within the manufacturing sector, critical factors to implement LSS, the role of LSS in the manufacturing sector from an implementation and sustainability viewpoint and Industry 4.0 viewpoints while highlighting the research gaps.

An SLR of 2,876 published articles extracted from Scopus, WoS, Emerald Insight, IEEE Xplore, Taylor & Francis, Springer and Inderscience databases was carried out following the protocol of systematic review. In total, 154 articles published in different journals over the past 10 years were selected for quantitative and qualitative analysis which revealed a number of research gaps.

The findings of the SLR revealed the growth of literature on LSS within the manufacturing sector. The review also highlighted the most cited critical success factors, critical failure factors, performance indicators and associated tools and techniques applied during LSS implementation. The review also focused on studies related to LSS and sustainability viewpoint and LSS and Industry 4.0 viewpoints.

The findings of this SLR can help senior managers, practitioners and researchers to understand the current developments and future requirements to adopt LSS in manufacturing sectors from sustainability and Industry 4.0 viewpoints.

Academic publications in the context of the role of LSS in various research streams are sparse, and to the best of the authors’ knowledge, this paper is one of the first SLRs which explore current developments and future requirements to implement LSS from sustainability and Industry 4.0 perspective.