Within only a couple of years, Industry 40 made the transition from a potential buzzword with an uncertain future to a serious manufacturing concept that is adopted by a constantly increasing number of companies However, recent studies suggest that corporations struggle with the transitional process or even hesitate to implement Industry 40 at all As a consequence, several investigations examined the potential factors that influence the implementation of Industry 40 Yet a comprehensive view of the issue cannot be formed because the findings are spread throughout a number of publications, and no single study has attempted to synthesize previous investigations Therefore, this study sets out to build a solid foundation for future research and to provide orientation for practitioners and governmental institutions by building a bridge between what already has been explored and by showing how the Systems Thinking perspective can help to get a better understanding of the complex nature of Industry 40 Based on a systematic literature review, this study presents and discusses a comprehensive list of potential factors that influence the implementation of Industry 40 and strengthens the idea that further research is necessary in order to address contradictory findings and to develop efficient Industry 40 implementation frameworks

The implementation of industry 4.0 – a systematic literature review of the key factors

Income over service life cost – Estimation of individual profitability of dairy cows at time of death reveals farm-specific economic trade-offs.

Complex thinking is a cognitive skill that focuses on the integrated analysis and synthesis of information with a systemic and critical perspective that enables creative decision-making in the face of complex realities or challenges. At the educational level, it is valued as a transdisciplinary competency, meaning it is relevant for individuals regardless of their profession or field of study. This article presents the results of measuring the perceived achievement of complex thinking among 830 graduating students from a technological university in Mexico, aiming to identify possible significant differences based on their discipline or major. Methodologically, a multivariate descriptive statistical analysis was performed using R and RStudio software, including calculation of means and standard deviations, violin plots, boxplot and ANOVA significance analysis, and t-test. The results show that the differences were not statistically significant in all the disciplines, although it is possible to note significant differences, which reveals a differentiated behavior in the process of formation and development of complex thinking according to the discipline of study. In conclusion, the present study shows that the students’ areas of training are associated with differences in perception of complex thinking and its associated sub-competencies, thus differentiating this ability in their graduation profile. This article contributes to the existing literature on the formation and development of complex thinking and its sub-competencies as relevant professional skills for lifelong learning.

Perception of the Level of Competency of Candidates for Graduation: A Multidisciplinary Approach to Complex Thinking

Scaffolding is becoming an increasingly common concept in transdisciplinary research. However, there is some uncertainty about what scaffolding as a practice means for the research process, other than the wide-ranging use of tools and facilitated methods. In this chapter, we start from a societal need to co-create knowledge for complex thinking on complex issues as we argue that learning is central and that scaffolding has an important role to play in promoting learning as both process and process outcome. The chapter examines scaffolding both as metaphor and practice, and how these perspectives of scaffolding have bearings on transdisciplinary projects. We build our discussion from two components: an imaginary walk on the construction site and diverse principles and practices for complex thinking taken from varying disciplinary discourse where collaborative processes are central. We continue by developing a model for scaffolding from a systemic approach - a learning system - based on previous learning models. The chapter concludes with a discussion on the promises and pitfalls of scaffolding in transdisciplinary research and how scaffolding opens new avenues for transdisciplinary processes. 

https://www.elgaronline.com/downloadpdf/book/9781802207835/book-part-9781802207835-10.pdf

The promise of scaffolding: a metaphor and living practice for transdisciplinary inquiry

To sustain the economic viability of a livestock farm in a global market, characterised by a price undercutting competition, farmers are forced to adapt to what the market demands. At the same time, they have to care for the functionality of the farm system as a whole and of the subsystems, such as the farm animals, so that they for their part they can contribute to an economic success. Now, that animal health and welfare (AHW) has become an increasingly important issue for citizens and consumers, not only the decision makers but also the disciplines of animal science are challenged to improve an unsatisfying AHW level that has been neglected for long. However, to reduce AHW problems requires a quite different approach than to increase productive efficiency. A common sense can be assumed concerning the need to strive for an optimal cost-to-benefit ratio while balancing positive and negative impacts of production processes on economic and AHW target figures. However, what is often not adequately considered is the fact that economic and biological demands have to be balanced within a living system, e.g. in the individual animal and farm system. These function as the relevant reference systems in all cases where measures to reduce AHW problems are considered. Furthermore, there is a large gap of scientific knowledge, however, not in the traditional sense. While the predominant approaches, scientists generate context-invariant, and thus generalisable disposal knowledge in diversified subdisciplines, problem solving requires contextualisation, orientation and action-guiding knowledge within transdisciplinary approaches. The reason is that AHW problems are highly context-sensitive as well as multifactorial. They develop within the farm specific interconnectedness of manifold and highly varying factors, emerging a complexity that does not allow predictive statements via inductive approaches but requires an iterative procedure to approach to a farm specific AHW level, which is balanced with the overarching goal of economic viability. Recommended action guiding knowledge has to be of high external and ecological validity, before farmers might consider it to be implemented in farm practice. From the reflection about the discrepancy between the knowledge needed to reduce AHW problems and what is offered by animal science, it is concluded that not only the farm systems but also the predominant approaches of animal science have to be transformed. Otherwise, there is not a big chance to considerably reduce AHW problems in farm animals.

Why has animal science not led to improved farm animal health and welfare?

The rise of complexity sciences has led to the development of new language about systems. Concepts such as ?complex systems thinking? or ?complexity thinking? have appeared in the literature, appealing to ways of thinking (in) complexity. The notion of ?complex thinking,? may be considered as referring to a mode of thinking more congruent with the complexity of the world. The widespread and sometimes undifferentiated usage of these concepts results in a lack of clarity and terminological confusion, which jeopardizes their heuristic and pragmatic value. We identify literature using terms related to thinking (in) complexity and use a combination of computational and qualitative methods to extract definitions and analyse their usage. We map the relationships of the concepts and their usage across different intellectual communities. Our goal is to clarify these concepts and to strengthen their pragmatic value for the promotion and management of positive changes in complex systems.

/pdf/thinking-in-complexity-in-definitions-and-mis-conceptions-42uc8pdq5o.pdf

Thinking (in) complexity : (In) definitions and (mis)conceptions

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Thinking (in) complexity : (In) definitions and (mis)conceptions