Assessment of essential competencies of open university students in Thailand for the sustainable smart manufacturing industry

The necessity for decreasing the negative impact of the manufacturing industry has recently increased. This is getting recognized as a global challenge due to the rapid increase in life quality standards, demand, and the decrease in available resources. Thus, manufacturing, as a core of the product provision system and a fundamental pillar of civilized existence, is significantly influenced by sustainability issues. Furthermore, current manufacturing modeling and assessment criteria require intensive revisions and upgrades to keep up with these new challenges. Nearly all current manufacturing models are based on the old paradigm, which was proven to be inadequate. Therefore, manufacturing technology, along with culture and economy, are held responsible for providing new tools and opportunities for building novel resolutions towards a sustainable manufacturing concept. One of such tools is sustainability assessment measures. Revising and updating such tools is a core responsibility of the manufacturing sector to efficiently evaluate and enhance sustainable manufacturing performance. These measures should be adequate to respond to the growing sustainability concerns in pursuit of an integrated sustainability concept. The triple bottom line (TBL) that includes environment, economic, and social dimensions has usually been used to evaluate sustainability. However, there is a lack of standard sets of sustainable manufacturing performance measures. In addition to the sustainability concept, a new concept of smart manufacturing is emerging. The smart manufacturing concept takes advantage of the recent technological leap in Artificial Intelligent (AI), Cloud Computing (CC), and the Internet of Things (IoT). Although this concept offers an important step to boost the current production capabilities to meet the growing need, it is still not clear whether the two concepts of smart manufacturing and sustainability will constructively or destructively interact. Therefore, the current study aims to integrate the sustainable smart manufacturing performance by incorporating sustainable manufacturing measures and discussing current and future challenges that are faced by the manufacturing sector. In addition, the opportunities for future research incorporating sustainable smart manufacturing are also presented.

BackgroundAs obesity increases, middle-income countries are undergoing a health-risk transition. We examine the association between socioeconomic status (SES) and emerging obesity in Thailand, and ascertain if an inverse relationship between SES and obesity has appeared.MethodsThe data derived from 87 134 individuals (54% female; median age, 29 years) in a national cohort of distance-learning Open University students aged 15–87 years and living throughout Thailand. We calculated adjusted odds ratios for associations of SES with obesity (body mass index, ≥25) across 3 age groups by sex, after controlling for marital status, age, and urbanization.ResultsObesity increased with age and was more prevalent among males than females (22.7% vs 9.9%); more females were underweight (21.8% vs 6.2%). Annual income was 2000 to 3000 US dollars for most participants. High SES, defined by education, income, household assets, and housing type, associated strongly with obesity—positively for males and inversely for females—especially for participants younger than 40 years. The OR for obesity associated with income was as high as 1.54 for males and as low as 0.68 for females (P for trend <0.001).ConclusionsOur national Thai cohort has passed a tipping point and assumed a pattern seen in developed countries, ie, an inverse association between SES and obesity in females. We expect the overall population of Thailand to follow this pattern, as education spreads and incomes rise. A public health problem of underweight females could emerge. Recognition of these patterns is important for programs combating obesity. Many middle income countries are undergoing similar transitions.

At present the development of critical thinking is crucial for individuals who are eager to get involved into productive interaction with the outside world, who are able to assess their own achievements objectively throughout the learning process, to analyze ways resulting in successes or fails, set purposes for self-improvement and self-development. There is a growing literature in medical education suggesting that reflection improves learning and performance in essential competencies to a growing literature in medical education suggesting that reflection improves learning and performance in essential competencies. Therefore fostering students’ reflective thinking is an important component of the educational process. The purpose of this study is to provide the grounds for organizing reflective activities for the future healthcare professionals in the context of their professional training. The experiment included 90 second-year students of Dentistry Faculty divided into two groups: test group involved 50 respondents and control group comprised 40 students. The method of studying reflexive abilities was based on applying teachers’ assessment and students’ self-assessment of students’ educational and cognitive activities including the following structural components: awareness of the learning outcomes and whether the outcomes are consisted with intended goals, self-analysis and self-assessment of individual activities and activities during team working. Each component was evaluated by five-score scale. Teachers also used the method of reflexive polylogue. The probability of the difference between the groups was determined by Student's t test. Designing of effective reflection requires time, effort and willingness; such activity should not feel like busy work or an add-on activity. The article elucidates the ways and principles of organization of reflective activity for future doctors. We offered some types of exercises aimed at developing the reflective skills for further professional work. We also detailed methodological recommendations and technoques on the organization of reflective activity for the dental students. The study has demonstrated that the highest level of reflexive skills in students corresponded to 3.4±0.7 scores that are quit sufficient for productive learning. It is through reflection the methods and results of own learning outomes are analyzed and assessed. Reflection is a skill, which requires development and can be applied broadly in medical education.

PurposeThis paper proposes strategies for adopting Industry 4.0 in achieving sustainable manufacturing, by overcoming barriers in the Sri Lankan manufacturing sector.Design/methodology/approachA conceptual model of sustainable manufacturing and Industry 4.0 was proposed based on a comprehensive literature review and validated through experts' inputs. The model was illustrated using three case studies to assess the relationships between sustainable manufacturing and Industry 4.0 in the Sri Lankan manufacturing context. Furthermore, possible strategies were proposed to overcome current barriers identified from case studies.FindingsThe case studies showcase that there is a considerable gap in Industry 4.0-enabled sustainable manufacturing in the Sri Lankan manufacturing sector due to several barriers. Thus, experts' knowledge-based strategies to overcome those barriers are proposed.Research limitations/implicationsThe conceptual model provides a holistic view of maturity levels of sustainable manufacturing measures directly connected with Industry 4.0 technologies. The study was limited to investigating the application of Industry 4.0 for sustainable manufacturing in leading apparel manufacturing organisations in Sri Lanka.Practical implicationsThe conceptual model can be used as a framework to guide practitioners in implementing Industry 4.0-enabled sustainable manufacturing. The proposed strategies in addressing barriers to Industry 4.0 adoption towards sustainable manufacturing can be directly applied to achieving better sustainable manufacturing performance.Originality/valueThis study is an informative guide to encourage the Sri Lankan manufacturing industry to adopt Industry 4.0 technologies in achieving sustainable manufacturing, using the knowledge of relationships between Industry 4.0 and three dimensions of sustainable manufacturing, possible barriers and strategies.

Fostering student competencies and perceptions through artificial intelligence of things educational platform

In this article, we cumulate previous research findings indicating that cyber-physical production systems bring about operations shaping social sustainability performance technologically. We contribute to the literature on sustainable cyber-physical production systems by showing that the technological and operations management features of cyber-physical systems constitute the components of data-driven sustainable smart manufacturing. Throughout September 2020, we performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “sustainable industrial value creation”, “cyber-physical production systems”, “sustainable smart manufacturing”, “smart economy”, “industrial big data analytics”, “sustainable Internet of Things”, and “sustainable Industry 4.0”. As we inspected research published only in 2019 and 2020, only 323 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, we decided upon 119, generally empirical, sources. Future research should investigate whether Industry 4.0-based manufacturing technologies can ensure the sustainability of big data-driven production systems by use of Internet of Things sensing networks and deep learning-assisted smart process planning.

When developing a method of sustainable manufacturing, it is important to take into account the three most important aspects of sustainability. The factors to take into consideration are the effects on the environment, the economy, and the society. The application of the various technologies that are part of Industry 4.0 has a significant amount of promise to pioneer sustainable production. It has been demonstrated that traditional methods of industry are detrimental to both society and the environment. This has made it even more crucial to transition to environmentally friendly practices. Industry 4.0 and the technologies that comprise its components, such as cloud computing, big data, the Internet of Things, etc., provide tremendous potential for enhancing manufacturing competitiveness. Today's E-Commerce businesses create vast quantities of data that may be utilized to make informed decisions and enhance client retention and acquisition prospects. However, the majority of E-commerce small and medium-sized businesses (SMEs) struggle with a lack of infrastructure to exploit data and its possibilities. This paper aims to demonstrate that Cloud computing may be utilized in a variety of ways to facilitate simple and accurate data analytics and procedures. In addition, this article includes a comparison between sustainable manufacturing and industry 4.0 technologies and their prospective effects on sustainable manufacturing.

Blockchain-empowered sustainable manufacturing and product lifecycle management in industry 4.0: A survey

A big data-driven framework for sustainable and smart additive manufacturing

Abstract: This chapter explores the transformative impact of AI-driven smart robotics in the manufacturing industry, focusing on how these advanced systems enhance production efficiency, optimize processes, and reshape the manufacturing landscape. It begins with an overview of the evolution of manufacturing automation, leading to the integration of AI, machine learning, and advanced sensor technologies in modern robotics. The chapter delves into the core components of smart robotics, including the integration of AI for predictive maintenance, quality control, and process optimization, as well as the use of sensors for real-time perception and adaptation. It also examines the role of collaborative robots (cobots) in enhancing human-robot collaboration and discusses the technical challenges, economic opportunities, and regulatory considerations associated with implementing smart robotics in manufacturing. The chapter concludes with a look at future trends, including the integration of emerging technologies like 5G and IoT, and the potential for smart robotics to drive sustainable and green manufacturing practices. Keywords: Smart Robotics, AI-Driven Automation, Manufacturing Efficiency, Collaborative Robots (Cobots), Predictive Maintenance, Quality Control, Process Optimization, Sensors in Robotics, Human-Robot Interaction (HRI), Sustainable Manufacturing, Industry 4.0, Cognitive Robotics, Real-Time Adaptive Control, 5G Connectivity, Internet of Things (IoT)and Edge Computing.

This study aims to analyse and determine the effect of Big Data, the Internet of Things (IoT), and physical-cyber system variables on human factors in refinery industry operators and the influence of human factors and managerial initiatives on sustainable manufacturing. The method used in this study is a quantitative method using partial least square-structural equation modelling (PLS-SEM). The respondents in this study were workers of Indonesia’s upstream oil and gas sector. The results of this study indicate that Big Data, IoT, and Physical Cyber Systems (PCS) have a positive and significant effect on the human factor. In addition, there is a significant relationship between human factors and sustainable manufacturing. Furthermore, it is also found that there is a relationship between managerial initiatives and sustainable manufacturing. However, the managerial initiative cannot moderate the human factor and sustainable manufacturing.

Industry 4.0 and the Internet of Things have revolutionized every manufacturing process, and the welding industry is far from this huge breakthrough. Big data and real-time monitoring as critical elements of the fourth industrial revolution are the essential parts of all manufacturing sectors, especially laser welding. Therefore, optimizing and controlling manufacturing processes using Industry 4.0 components, such as the Internet of Things, sensor-based monitoring, and big data analytics, are considered critical approaches toward sustainable, efficient, and defect-free manufacturing. In this regard, this chapter has argued intelligent laser welding and analyzed sustainable manufacturing challenges by using optimization approaches. It recommends possible concerted effort and reveals how laser welding and Industry 4.0 strategies can integrate, assist, and synchronize each other.KeywordsIndustry 4.0Laser welding 4.0Smart manufacturingSustainable manufacturingDigital twins

Air pollution, climate change, and chemical exposure constitute the world's most significant environmental health concern, resulting in the early deaths of 6. 5 million people annually. Reducing child mortality from preventable causes, primarily pneumonia and other respiratory illnesses, would have contributed to the united nation's sustainable development goals (SDG). Some significant goals are sustainable cities, industry innovation, green and resilient infrastructure, good health, and well-being. Non-ventilator hospital-acquired pneumonia (NV-HAP) is a severe but preventable cause of morbidity and mortality in hospitalized patients. Despite being the most frequent and fatal hospital-acquired infection (HAI), NV-HAP is not tracked, documented, or avoided in most hospitals. The success of NV-HAP prevention and monitoring initiatives relies on reliable, up-to-date surveillance data. Surveillance offers the information needed to target, analyze, and quantify the efficacy of preventative activities by identifying patients at the highest risk for NV-HAP. However, pneumonia monitoring is complex due to the clinical criteria's subjective, imprecise, inconsistently recorded, and labor-intensive nature. Non-ventilator hospital-acquired pneumonia must be monitored and standardized, which demands cutting-edge technologies and the deployment of advanced sensors. In the framework of this research, initially, a wireless body area networks (WBANs) architecture has built by making use of wearable biosensors, and then real-time sensor data were uploaded to a cloud platform. Researchers have devised a wireless sensor network (WSN) to track volatile organic compounds (VOC) and other atmospheric characteristics in real time to curb the spread of NV-HAP. The ESP32 Internet of Things (IoT) and Raspberry Pi 4B graphical processing unit platforms host the finalized WBAN and WSN network. To reduce the mortality rate of NV-HAP, this research aims to investigate clinics' and hospitals' indoor and outdoor air quality. The developed biosensor-assisted IoT enabled framework is used in hospitals to keep tabs on the conditions of individual patient rooms, treatment areas, and critical care units in real time. The research found the suggested technique achieves better results than existing state-of-the-art methods regarding computing cost, communication overhead, storage cost, and energy utilization.

Does lean and sustainable manufacturing lead to Industry 4.0 adoption: The mediating role of ambidextrous innovation capabilities

BackgroundCaregivers constitute an important informal workforce, often undervalued, facing challenges to maintain their caring role, health and wellbeing. Little is known about caregivers in middle-income countries like Thailand. This study investigates the physical and mental health of Thai adult caregivers.MethodsThis report derives from distance-learning students working and residing throughout Thailand and recruited for a health-risk transition study in 2005 (N=87,134) from Sukhothai Thammathirat Open University. The cohort follow-up questionnaire in 2009 (N = 60,569) includes questions on caregiver status which were not available in 2005; accordingly, this study is confined to analysis of the 2009 data. We report cross-sectional associations between caregiver status and health.ResultsAmong the study participants in 2009, 27.5% reported being part-time caregivers and 6.6% reported being full-time caregivers. Compared to male non-caregivers, being a part-time or full-time male caregiver was associated with lower back pain (covariate-Adjusted Odds Ratios, AOR 1.36 and 1.67), with poor psychological health (AOR 1.16 and 1.68), but not with poor self-assessed health. Compared to female non-caregivers, being a part- or full-time female caregiver was associated with lower back pain (AOR 1.47 and 1.84), psychological distress (AOR 1.32 and 1.52), and poor self-assessed health (AOR 1.21 and 1.34).ConclusionsAdult caregivers in Thailand experienced a consistent adverse physical and mental health burden. A dose–response effect was evident, with odds ratios higher for full-time caregivers than for part-time, and non-caregivers. Our findings should raise awareness of caregivers, their unmet needs, and support required in Thailand and other similar middle-income countries.