In today’s rapidly evolving technological landscape, the ability to bridge diverse fields of study is crucial for tackling the multifaceted challenges faced by industries. Generative Pre-trained Transformers (GPT), a breakthrough in artificial intelligence, exemplify this interdisciplinary potential. By seamlessly connecting industrial engineering, computer science, and other disciplines, GPT is driving innovation in areas where collaboration and integration are essential.

In this blog post, we will explore how GPT-based systems enable interdisciplinary applications, with a focus on their impact in human-computer interaction (HCI) and knowledge management. These applications align with Jurnal Optimasi Sistem Industri’s (JOSI) mission to foster interdisciplinary research and promote system optimization.

Industrial systems are rarely straightforward. They often involve complex, ill-structured problems influenced by human factors, organizational culture, and decision-making dynamics. These types of challenges, often addressed through soft systems methodologies, require innovative approaches to bridge gaps between technology, people, and processes. Generative Pre-trained Transformers (GPT), with their advanced natural language understanding capabilities, have emerged as a promising tool for optimizing soft systems in industrial engineering.

In this post, we explore how GPT can support soft systems methodologies by enhancing decision-making and facilitating effective communication among stakeholders.

Dear readers, the development of artificial intelligence has advanced to the point of daily application, impacting everyone from researchers to the general public. In line with this progress, Jurnal Optimasi Sistem Industri will explore how artificial intelligence, with a particular focus on Generative Pre-trained Transformers (GPT), aligns with the journal's focus and scope. We will publish a series of concise and accessible articles on this topic to ensure ease of reading and understanding.

We begin with this post: Exploring the Relevance of GPT in Industrial Engineering

Enjoy!

Dear valued visitors, readers, authors, and reviewers,

We are excited to share that Jurnal Optimasi Sistem Industri is now live on a new server! After encountering some challenges over the past few months, we are genuinely delighted to be able to serve you once again.

However, there is an important update. For security reasons, we were unable to transfer your old usernames and passwords to the new server. We sincerely apologize for any inconvenience this may cause and kindly ask for your understanding, as this step was taken to ensure the best for all of us.

We humbly request that you register your account again on the new server. Once again, we deeply regret any inconvenience this might bring, but we are confident this measure will lead to a better and more secure experience for the future.

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We greatly appreciate your understanding and apologize for any disruption caused. Thank you for your continued support and cooperation.

In recent years, sustainability has become a central concern for industries worldwide. The drive toward eco-friendly practices, reducing environmental impact, and adopting long-term environmental responsibility has led to the rethinking of industrial systems. While much attention is given to the technical innovations that reduce waste and improve efficiency, the role of soft systems—such as leadership, team collaboration, and decision-making—is equally important in promoting sustainability. Soft systems provide the human-driven elements that guide an organization’s sustainability efforts, ensuring that eco-friendly practices are not only implemented but sustained over time. This post explores how optimizing soft systems can play a key role in fostering sustainable industrial operations.

In the evolving landscape of industrial systems, the role of technology has become increasingly vital, not only in enhancing the efficiency of hard systems but also in optimizing soft systems. Soft systems, which encompass human-centered aspects such as decision-making, leadership, and communication, are crucial to the overall performance of industrial operations. As industries adopt more sophisticated technologies like artificial intelligence (AI), automation, and communication platforms, the potential to improve the effectiveness of these human-centered systems becomes immense. In this post, we’ll explore how technology can be leveraged to optimize soft systems, enhancing decision-making, communication, and leadership in industrial environments.

In the previous post, we explored how optimizing soft systems can enhance decision-making and collaboration in industrial settings. Now, we’ll take a closer look at how soft systems can contribute to creating a culture of continuous improvement and how strong leadership plays a crucial role in sustaining optimized soft systems. Both factors are essential for driving long-term success in industrial environments.

For the next post in the series, we will explore the concept of industrial systems, with a particular focus on soft systems. Soft systems are an integral part of modern industrial processes, particularly in complex environments where human factors, organizational structures, and non-quantifiable elements play significant roles in decision-making and optimization.

This post is part of the series that will explore the optimisation concept, tailored for authors and researchers interested in submitting to Jurnal Optimasi Sistem Industri (JOSI). We will break down essential optimization techniques and terminologies, providing insights that can guide your research and manuscript preparation, helping you align with the scope and standards of JOSI.