How artificial intelligence can be used to improve lean manufacturing and production processes

The implementation of Lean and Artificial Intelligence has demonstrated a positive correlation across different industries. By integrating AI techniques, the efficiency and effectiveness of Lean processes can be enhanced. The combination of Lean and AI contributes to improved decision-making, increased productivity, and reduced waste. Moreover, AI can identify and rectify process errors, enabling streamlined and more efficient operations. In 2014, Hennig Olsen initiated the implementation of lean thinking, which yielded mixed results initially. However, they decided to adopt lean principles according to their specific requirements, leading to significantly improved outcomes. With the rapid advancement of technology, Hennig Olsen ventured into experimenting with artificial intelligence, particularly in the realm of vision control, starting in 2019. Subsequently, they have consistently embraced and integrated increasingly advanced technologies to continuously enhance their production lines. This case study examined the impact of implementing artificial intelligence on the company's performance. The findings revealed that as Hennig Olsen incorporated more artificial intelligence into their production lines, they experienced a significant reduction in customer complaints. However, they continue to face challenges in meeting their overall equipment effectiveness goals. The thesis also identified potential areas for improvement, emphasizing the potential benefits of integrating six sigma processes through AI initiatives. More specifically, implementing predictive maintenance to minimize unexpected downtime and improve OEE emerged as a key opportunity. Leveraging AI to analyze vast amounts of data could also prove advantageous in optimizing cycle time and reducing waste within the organization. Finally, this report has examined the readiness of Hennig Olsen to further integrate AI tools into their operations. To fully capitalize on the potential benefits of AI and evolve into a comprehensive smart factory, the company needs to invest in additional technologies such as the Internet of Things, big data analytic, and cloud computing. However, a significant hurdle arises from the limitations of their existing machinery, which cannot gather extensive data or establish interconnectivity. Moreover, sourcing qualified personnel proficient in developing these technologies poses a challenge. A more effective strategy, along with support from stakeholders, is necessary to encourage investments in new technologies. This will facilitate the successful implementation of AI technologies and foster improved acceptance of new technology among employees

How artificial intelligence can be used to improve lean manufacturing and production processes A case study of Hennig Olsen

The implementation of Lean and Artificial Intelligence has demonstrated a positive correlation across different industries. By integrating AI techniques, the efficiency and effectiveness of Lean processes can be enhanced. The combination of Lean and AI contributes to improved decision-making, increased productivity, and reduced waste. Moreover, AI can identify and rectify process errors, enabling streamlined and more efficient operations. In 2014, Hennig Olsen initiated the implementation of lean thinking, which yielded mixed results initially. However, they decided to adopt lean principles according to their specific requirements, leading to significantly improved outcomes. With the rapid advancement of technology, Hennig Olsen ventured into experimenting with artificial intelligence, particularly in the realm of vision control, starting in 2019. Subsequently, they have consistently embraced and integrated increasingly advanced technologies to continuously enhance their production lines. This case study examined the impact of implementing artificial intelligence on the company’s performance. The findings revealed that as Hennig Olsen incorporated more artificial intelligence into their production lines, they experienced a significant reduction in customer complaints. However, they continue to face challenges in meeting their overall equipment effectiveness goals. The thesis also identified potential areas for improvement, emphasizing the potential benefits of integrating six sigma processes through AI initiatives. More specifically, implementing predictive maintenance to minimize unexpected downtime and improve OEE emerged as a key opportunity. Leveraging AI to analyze vast amounts of data could also prove advantageous in optimizing cycle time and reducing waste within the organization. Finally, this report has examined the readiness of Hennig Olsen to further integrate AI tools into their operations. To fully capitalize on the potential benefits of AI and evolve into a comprehensive smart factory, the company needs to invest in additional technologies such as the Internet of Things, big data analytic, and cloud computing. However, a significant hurdle arises from the limitations of their existing machinery, which cannot gather extensive data or establish interconnectivity. Moreover, sourcing qualified personnel proficient in developing these technologies poses a challenge. A more effective strategy, along with support from stakeholders, is necessary to encourage investments in new technologies. This will facilitate the successful implementation of AI technologies and foster improved acceptance of new technology among employees

Comparison between the two definitions of AI

Two different definitions of the Artificial Intelligence concept have been proposed in papers [1] and [2]. The first definition is informal. It says that any program that is cleverer than a human being, is acknowledged as Artificial Intelligence. The second definition is formal because it avoids reference to the concept of human being. The readers of papers [1] and [2] might be left with the impression that both definitions are equivalent and the definition in [2] is simply a formal version of that in [1]. This paper will compare both definitions of Artificial Intelligence and, hopefully, will bring a better understanding of the concept.Comment: added four new section

Professional Judgment in an Era of Artificial Intelligence and Machine Learning

Though artificial intelligence (AI) in healthcare and education now accomplishes diverse tasks, there are two features that tend to unite the information processing behind efforts to substitute it for professionals in these fields: reductionism and functionalism. True believers in substitutive automation tend to model work in human services by reducing the professional role to a set of behaviors initiated by some stimulus, which are intended to accomplish some predetermined goal, or maximize some measure of well-being. However, true professional judgment hinges on a way of knowing the world that is at odds with the epistemology of substitutive automation. Instead of reductionism, an encompassing holism is a hallmark of professional practice—an ability to integrate facts and values, the demands of the particular case and prerogatives of society, and the delicate balance between mission and margin. Any presently plausible vision of substituting AI for education and health-care professionals would necessitate a corrosive reductionism. The only way these sectors can progress is to maintain, at their core, autonomous professionals capable of carefully intermediating between technology and the patients it would help treat, or the students it would help learn

Wittgenstein and Communication Technology : A conversation between Richard Harper and Constantine Sandis

Special Issue: PROCEEDINGS OF THE BRITISH WITTGENSTEIN SOCIETY 10TH ANNIVERSARY CONFERENCE: WITTGENSTEIN IN THE 21ST CENTURY © 2018 John Wiley & Sons LtdThis paper documents a conversation between a philosopher and a human computer interaction researcher whose research has been enormously influenced by Wittgenstein. In particular, the in vivo use of categories in the design of communications and AI technologies are discussed, and how this meaning needs to evolve to allow creative design to flourish. The paper will be of interest to anyone concerned with philosophical tools in everyday action.Non peer reviewe