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This study aims to explore the integration of Industry 4.0 technologies with lean six sigma practices in the manufacturing sector for enhanced process improvement.

This study used a fuzzy decision-making trial and evaluation laboratory approach to identify critical Industry 4.0 technologies that can be harmonized with Lean Six Sigma methodologies for achieving improved processes in manufacturing.

The research reveals that key technologies such as modeling and simulation, artificial intelligence (AI) and machine learning, big data analytics, automation and industrial robots and smart sensors are paramount for achieving operational excellence when integrated with Lean Six Sigma.

The study is limited to the identification of pivotal Industry 4.0 technologies for Lean Six Sigma integration in manufacturing. Further studies can explore the implementation challenges and the quantifiable benefits of such integrations.

Integrating Industry 4.0 technologies with Lean Six Sigma enhances manufacturing efficiency. This approach leverages AI for predictive analysis, uses smart sensors for energy efficiency and adaptable robots for flexible production. It is vital for competitive advantage, significantly improving decision-making, reducing costs and streamlining operations in the manufacturing sector.

The integration of Industry 4.0 technologies with Lean Six Sigma in manufacturing has significant social implications. It promotes job creation in high-tech sectors, necessitating advanced skill development and continuous learning among the workforce. This shift fosters an innovative, knowledge-based economy, potentially reducing the skills gap. Additionally, it enhances workplace safety through automation, reduces hazardous tasks for workers and contributes to environmental sustainability by optimizing resource use and reducing waste in manufacturing processes.

This study offers a novel perspective on synergizing advanced Industry 4.0 technologies with established Lean Six Sigma practices for enhanced process improvement in manufacturing. The findings can guide industries in prioritizing their technological adoptions for continuous improvement.

This paper aims to study the extent of the transformation of European manufacturing companies towards the factory of the future (FoF) and related concepts, e.g. Industry 4.0 and digitalisation.

A qualitative survey design was used to investigate the areas, patterns and elements for implementing FoF. A total of 92 responses from manufacturing firms of Alpine regions were collected and analysed, followed by in-depth interviews with a subset of respondents to identify common challenges, drivers and opportunities for the transformation.

Manufacturing companies are gaining awareness on their needs and gaps in the FoF path, the implications on business strategy and the rates of innovation and technology adoption. Nevertheless, they still need to shape their organisational structures (e.g. from highly centralised to more collaborative ones) and nurture their managerial capabilities in operations and supply chain management, and customer relationships, only partially based on FoF technologies.

This study aims to contribute to recent literature and practice of FoF (and related concepts) by depicting a picture of the possible areas of intervention, main issues and gaps (especially in terms of skills, supply chain and customer relationships) of manufacturing companies in their digital transformation. The qualitative research design and its scope represent the main limitations.

This paper provides a systemic overview for FoF by encompassing the technological, strategic, managerial and organisational perspectives of digitalisation in manufacturing and integrating the insights from a multi-sectorial and multi-dimensional analysis.

Knowing the students' readiness for the fourth industrial revolution (4IR) is essential to producing competent, knowledgeable and skilled graduates who can contribute to the skilled workforce in the country. This will assist the Higher Education Institutions (HEIs) to ensure that their graduates own skill sets needed to work in the 4IR era. However, studies on students' readiness and preparedness for the 4IR in developing countries such as the Sultanate of Oman are still lacking. Therefore, this study investigates students' readiness level and preparedness for the 4IR. The findings of this study will benefit the HEIs policymakers, administration, faculties, departments, industries and society at large since they will be informed of the student's readiness and preparedness toward industry 4.0.

The authors adopted the measures from the same context as previous studies in this study. The questionnaire was divided into three sections; the first part described the purpose and introduction of the search with the surety to keep the data confidential. The second part consisted of demographical information like gender, education. The last parts consisted of four subsections, question items in these parts are based on the related previous study. Characteristics consisted of 14 items, knowledge consisted of 18 items related to 4IR technologies, Organizational Dimension comprised of four items related to academic programs, curriculum and training. Preparedness contained two items. The participants have rated all the items in 5-Likert scale.

Results from structural equation modeling showed that students' characteristics, knowledge of 4IR technologies and organizational dimensions significantly impact their preparedness for the 4IR. The study also found that organizational dimensions have the highest impact on students' preparedness. Furthermore, the organizational dimension significantly influences students' knowledge of 4IR technology. Moreover, students' characteristics related to 4IR are significantly affected by their knowledge of 4IR technology and organizational dimension. The findings suggest that HEIs are responsible for increasing the adoption of 4IR, and therefore organizational dimensions such as the academic programs, training, technological infrastructure and others are all critical for preparing students for a better future and should be given a priority.

This study has used academic programs and training to measure the organizational dimension. However, other important factors should be considered, such as technological infrastructure and leadership and governance of HEIs. Second, the current research depends on quantitative data, so future research should implement a mixed methodology (questionnaires, depth interviews, document analysis and focus group) to understand the factors affecting students' readiness for 4IR clearly. Finally, although the 4IR has numerous benefits, it also has challenges in its implementation, so future studies should focus on challenges encountered by different stakeholders in implementing 4IR-related technologies.

The curriculum must include mandatory courses related to IT infrastructure design, user experience programming, electronic measurement and control principles, and programming for data science. HEIs should also foster interdisciplinary knowledge by integrating IT, Engineering, Business and Sciences. Furthermore, the HEIs should develop their infrastructure to have smart campuses, labs, classrooms and libraries to make HEIs a space where knowledge can be generated and innovative solutions can be proposed. This entails HEIs offering necessary hardware, software and technical support because if the HEIs improve their technological resources, students will be capable of using 4IR-related technologies effectively.

The advancement of technology has resulted in the emergence of the Fourth Industrial Revolution (4IR), such as artificial intelligence, blockchain, robotics, cloud computing, data science, virtual reality and 3D printing. It is essential to investigate students' readiness for 4IR. However, there is no study as per researchers' knowledge talked about students readiness in HEIs in the Arab world. This study could be a basis for more research on students' perception of the 4IR covering students from various backgrounds and levels.

The world is changing fast and pace of changes that are being observed since start of the twenty-first century have never been observed before. Due to such changes and their impact, world is described in terms of Volatile, Uncertain, Complex and Ambiguous (VUCA). The trend of industry 4.0 is also said to be an another contributing factor into the VUCA environment. The VUCA creates a lot of challenges for organization from the perspective of management and leadership. Both business and leadership agility are needed more than VUCA as the VUCA world is becoming old. Therefore, the purpose of this research is to review the literature and to summarize the understanding with regard to managing VUCA-RR world in an era of Industry 4.0. Since the advent of term VUCA, many researchers have provided theoretical model and framework to guide managers regarding to their action and strategies. But, current research postulates based upon the literature that agile management’s tools and techniques are highly effective in managing the situation of VUCA-RR in the era of Industry 4.0. The research concludes that Industry 4.0 together with VUCA-RR and indecently possess to change management challenges to organizations. The organization can be in better position to manage change management challenges posed by Industry 4.0 by implementing the agile management. The Industry 4.0 will latter compliment to agile management tools and techniques which will make any organization to become a better equipped to face the VUCA-RR world. The research has also concluded that agile management powered by Industry 4.0 enabling technologies presents enormous opportunity in the form of VUCA 2.0 (Vision, Understanding, Courage, Adoptability, Rapidity and Radicality) that can be used to square off the effect of VUCA-RR world.

The purpose of this article is to propose and evaluate a novel system architecture for Smart City applications which uses ontology reasoning and a distributed stream processing framework on the cloud. In the domain of Smart City, often methodologies of semantic modeling and automated inference are applied. However, semantic models often face performance problems when applied in large scale.

The problem domain is addressed by using methods from Big Data processing in combination with semantic models. The architecture is designed in a way that for the Smart City model still traditional semantic models and rule engines can be used. However, sensor data occurring at such Smart Cities are pre-processed by a Big Data streaming platform to lower the workload to be processed by the rule engine.

By creating a real-world implementation of the proposed architecture and running simulations of Smart Cities of different sizes, on top of this implementation, the authors found that the combination of Big Data streaming platforms with semantic reasoning is a valid approach to the problem.

In this article, real-world sensor data from only two buildings were extrapolated for the simulations. Obviously, real-world scenarios will have a more complex set of sensor input values, which needs to be addressed in future work.

The simulations show that merely using a streaming platform as a buffer for sensor input values already increases the sensor data throughput and that by applying intelligent filtering in the streaming platform, the actual number of rule executions can be limited to a minimum.

Data acquisition and data fusion of large numbers of sensors present unique challenges for control systems designers and applications engineers alike. In recent years the sensors industry has been moving towards the use of smart sensors, fieldbus networks, and localized smart processes. Merritt Systems Inc. of Rockledge, Florida, has been in the forefront of these developments since 1987 when it started pursuing the development of large sensor networks for robotic obstacle avoidance. As a result of this work a number of unique smart sensors and network technologies have been developed which have a wide range of applications beyond robotics. These include: one of industry’s first smart sensors, smart sensor networks, PC‐based data acquisition and control systems, and novel robotic modelling and motion planning algorithms. Whenever large networks of sensors with mixed sensing media are used, this technology has far‐reaching applications to industry and the research community.

Internet has changed radically in the way people interact in the virtual world, in their careers or social relationships. IoT technology has added a new vision to this process by enabling connections between smart objects and humans, and also between smart objects themselves, which leads to anything, anytime, anywhere, and any media communications. IoT allows objects to physically see, hear, think, and perform tasks by making them talk to each other, share information and coordinate decisions. To enable the vision of IoT, it utilizes technologies such as ubiquitous computing, context awareness, RFID, WSN, embedded devices, CPS, communication technologies, and internet protocols. IoT is considered to be the future internet, which is significantly different from the Internet we use today. The purpose of this paper is to provide up-to-date literature on trends of IoT research which is driven by the need for convergence of several interdisciplinary technologies and new applications.

A comprehensive IoT literature review has been performed in this paper as a survey. The survey starts by providing an overview of IoT concepts, visions and evolutions. IoT architectures are also explored. Then, the most important components of IoT are discussed including a thorough discussion of IoT operating systems such as Tiny OS, Contiki OS, FreeRTOS, and RIOT. A review of IoT applications is also presented in this paper and finally, IoT challenges that can be recently encountered by researchers are introduced.

Studies of IoT literature and projects show the disproportionate importance of technology in IoT projects, which are often driven by technological interventions rather than innovation in the business model. There are a number of serious concerns about the dangers of IoT growth, particularly in the areas of privacy and security; hence, industry and government began addressing these concerns. At the end, what makes IoT exciting is that we do not yet know the exact use cases which would have the ability to significantly influence our lives.

This survey provides a comprehensive literature review on IoT techniques, operating systems and trends.