Traditional engineering instruction is deductive, beginning with theories and progressing to the applications of those theories Alternative teaching approaches are more inductive Topics are introduced by presenting specific observations, case studies or problems, and theories are taught or the students are helped to discover them only after the need to know them has been established This study reviews several of the most commonly used inductive teaching methods, including inquiry learning, problem-based learning, project-based learning, case-based teaching, discovery learning, and just-in-time teaching The paper defines each method, highlights commonalities and specific differences, and reviews research on the effectiveness of the methods While the strength of the evidence varies from one method to another, inductive methods are consistently found to be at least equal to, and in general more effective than, traditional deductive methods for achieving a broad range of learning outcomes

Inductive Teaching and Learning Methods: Definitions, Comparisons, and Research Bases

THE NEED FOR QUALITY The first thing that we need to consider, in any organization, is that quality is the most important thing. The quality of your work defines you.  Whoever you are,  Whatever you do,  I can find the same products and services cheaper somewhere else. But your quality is your signature. Developing and delivering high quality products and services means that you are doing things correctly from the beginning. As a consequence, you are reducing the need for additional services, from verification to warranty.

Total quality management.

Purpose - This paper aims to investigate the definition of Lean Production and the methods and goals associated with the concept as well as how it differs from other popular management concepts. Methodology/Approach - The paper is based on a review of the contemporary literature on Lean Production, both journal articles and books. Findings - It is shown in the paper that there is no consensus on a definition of Lean Production between the examined authors. The authors also seem to have different opinions on which characteristics that should be associated with the concept. Overall it can be concluded that Lean Production is not clearly defined in the reviewed literature. This divergence can cause some confusion on a theoretical level, but is probably more problematic on a practical level when organizations aim to implement the concept. This paper argues that it is important for an organization to acknowledge the different variations, and to raise the awareness of the input in the implementation process. It is further argued that the organization should not accept any random variant of Lean, but make active choices and adapt the concept to suit the organization-s needs. Through this process of adaptation, the organization will be able to increase the odds of performing a predictable and successful implementation. Originality/Value - This paper provides a critical perspective on the discourse surrounding Lean Production, and gives an input to the discussion of the implementation of management models. Keywords - Lean Production, Definition, Construct Validity, Total Quality Management Paper type - Conceptual paper

https://www.ep.liu.se/ecp/033/025/ecp0803325.pdf

Defining Lean Production : Some conceptual and practical issues

Markets and motor cars the automotive industries today shared technical change development of new automobiles customer-supplier relationships lean supply strategies for going lean what next?

https://link.springer.com/content/pdf/10.1057%2Fjors.1994.30.pdf

Beyond Partnership: Strategies for Innovation and Lean Supply

Entrepreneurial education is the process of providing individuals with the ability to recognise commercial opportunities and the insight, self-esteem, knowledge and skills to act on them. It includes instruction in opportunity recognition, commercialising a concept, marshalling resources in the face of risk, and initiating a business venture. It also includes instruction in traditional business disciplines such as management, marketing, information systems and finance. The purpose of this paper is to describe the design and introduction of a new program in Entrepreneurship at the University of Tasmania. Within this program the process and responsibility of learning has largely been reversed through the process of student centred learning. This method of learning represents a challenging departure from the traditional mainstream teaching practices. In considering the benefits achievable from this teaching method, this paper also considers the difficulties in transferring increased responsibility to students to manage their futures.

A contemporary approach to entrepreneurship education

With the arrival of new technologies in modern smart factories, automated predictive maintenance is also related to production robotisation. Intelligent sensors make it possible to obtain an ever-increasing amount of data, which must be analysed efficiently and effectively to support increasingly complex systems' decision-making and management. The paper aims to review the current literature concerning predictive maintenance and intelligent sensors in smart factories. We focused on contemporary trends to provide an overview of future research challenges and classification. The paper used burst analysis, systematic review methodology, co-occurrence analysis of keywords, and cluster analysis. The results show the increasing number of papers related to key researched concepts. The importance of predictive maintenance is growing over time in relation to Industry 4.0 technologies. We proposed Smart and Intelligent Predictive Maintenance (SIPM) based on the full-text analysis of relevant papers. The paper's main contribution is the summary and overview of current trends in intelligent sensors used for predictive maintenance in smart factories.

Predictive Maintenance and Intelligent Sensors in Smart Factory: Review.

Green processes are very important for the implementation of green technologies in production to achieve positive sustainability outcomes in the Industry 4.0 era. The scope of the paper is to review how conventional green processes as a part of Industry 4.0 provide sustainability outcomes in manufacturing. The paper is based on the methodology of systematic literature review through the content analysis of literary resources. Twenty-nine studies were included in our content analysis. The results show the main focus of current literature related to Industry 4.0, sustainability outcomes and green processes. The authors present a conceptual Sustainability Green Industry 4.0 (SGI 4.0) framework that helps to structure and evaluate conventional green processes in relation to Industry 4.0 and sustainability. The study summarizes which technologies (big data, cyber-physical systems, Industrial Internet of Things and smart systems) and green processes (logistics, manufacturing and product design) are important for achieving a higher level of sustainability. The authors found that the most often common sustainability outcomes are energy saving, emission reduction, resource optimalization, cost reduction, productivity and efficiency and higher economic performance, human resources development, social welfare and workplace safety. The study suggests implications for practice, knowledge and future research.

https://www.mdpi.com/2071-1050/12/15/5968/pdf

Sustainability Outcomes of Green Processes in Relation to Industry 4.0 in Manufacturing: Systematic Review

Sustainability has recently become a phenomenon; small and medium-sized enterprises (SMEs) are increasingly emphasizing the principles of sustainability in their corporate governance. They implement these changes through project management. The purpose of the paper is to determine the critical success factors in project management, as seen by the managers of Czech manufacturing enterprises, related to the most to the successful completion of the projects. We aim to analyze the relation of these success factors to Industry 4.0, Human Resources, and sustainability. We determined the possible interconnectedness of the critical success factors using correlation coefficients. Then, we compared them using the Mann-Whitney test with new corporate management trends. The results show that companies consider Leadership and Experiences, and Employees and Flexibility to be key factors in project management’s success. The most important critical factor for the sustainability of projects focused on Industry 4.0 is the finances that decide the implementation of projects. The benefits of Industry 4.0 concerning sustainability have been identified in projects aimed at implementing new energy sources. In addition to the results obtained, the development of a methodology for evaluating Industry 4.0 projects’ success concerning sustainability may be based on critical success factors in the future.

Critical Success Factors of the Project Management in Relation to Industry 4.0 for Sustainability of Projects

Due to Industry 4.0 technologies, small- and medium-sized enterprises have a great opportunity to increase their competitiveness. However, the question remains as to whether they are truly able to implement such modern technologies faster and carry out digital transformation. The main aim of the paper is to classify small- and medium-sized enterprises into various groups, according to the level of implementation of Industry 4.0, using the Index of Industry 4.0. Based on the results of the cluster analysis, the small and medium enterprises are categorized into four different groups, according to the level of implementation of Industry 4.0. There are top Industry 4.0 technological enterprises, I4 start enterprises, noobs enterprises, and I4 advances enterprises. So far, the largest group consists of the small- and medium-sized enterprises that are just starting out with the introduction of Industry 4.0 technologies, such as IT infrastructure, digitalization (data, cloud, data analysis, and information systems), and sensors. On the other hand, the top I4 technological enterprises group is the least numerous. The analysis carried out comparing the small- and medium-sized enterprises with the large enterprises shows that the SMEs still have a lower level of Industry 4.0 implementation. This confirms the assumption that the large enterprises have greater opportunities to use new technologies and transform them into smart factories. However, this situation may change in the future if new technologies become more accessible, and SMEs are worth investing in Industry 4.0 in terms of the return on investment.

Classification of small-and medium-sized enterprises based on the level of industry 4.0 implementation

Industry 4.0 includes digital process transformation, information technology (IT) development, mobile devices, learning software, automation, and robotics, as well as intelligent sensors to collect large datasets, store, analyze, and use them in business, including simulation, virtual reality, and digital twins. The aim of the paper is to characterize the readiness of the enterprise to use Industry 4.0. In the research, a questionnaire survey was carried out on a sample of 276 enterprises mainly from the manufacturing industry. Using explorative factor analysis, the index of Industry 4.0 (VPi4) was designed to determine the level of Industry 4.0 implementation in the enterprises. The results were further verified by a statistical analysis, using Mann–Whitney test and correlation coefficients. The results indicate that the VPi4 index was consistent in terms of distribution when comparing the results on the verification sample. Its results correlate with the subjective perception of the enterprises, and different levels of the index reflect the difference in technological intensity of the industry. The VPi4 index enables the enterprises to determine their own level of current state of readiness for Industry 4.0, to better prioritize business development. The proposed solution categorizes Industry 4.0 components into a useful theoretical framework. Further research offers the possibility of applying the index in other sectors, its relation to the size of enterprises, and updating with respect to new trends in information technology.

Martin Pech

Papers

Predictive Maintenance and Intelligent Sensors in Smart Factory: Review.

Sustainability Outcomes of Green Processes in Relation to Industry 4.0 in Manufacturing: Systematic Review

Critical Success Factors of the Project Management in Relation to Industry 4.0 for Sustainability of Projects

Classification of small-and medium-sized enterprises based on the level of industry 4.0 implementation

Readiness of Enterprises in Czech Republic to Implement Industry 4.0: Index of Industry 4.0