Interdisciplinary Applications of GPT: Bridging the Gap Between Technology and Industrial Engineering

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.

The Interdisciplinary Nature of GPT

GPT-based AI systems are inherently interdisciplinary. Their core strength lies in natural language processing (NLP), a capability rooted in computer science, but their applications extend far beyond this field. By interpreting and generating human language, GPT enables industries to streamline operations, enhance decision-making, and improve human-machine interactions. These systems can function as a bridge between technological tools and human users, making them particularly valuable for industrial engineering applications.

Let’s dive into two key areas where GPT demonstrates its interdisciplinary capabilities:

1. Human-Computer Interaction (HCI)

Human-Computer Interaction (HCI) is a critical field that focuses on designing systems that are intuitive, user-friendly, and efficient for human operators. In industrial engineering, HCI plays an essential role in ensuring that advanced technologies, such as automation and control systems, are accessible and effective for users at all levels of expertise.

GPT enhances HCI by:

- Facilitating Natural Language Interfaces: GPT enables machines to understand and respond to user commands in natural language, removing the need for complex coding or technical jargon. This improves accessibility for operators who may not have advanced technical training.
- Enabling Context-Aware Interactions: By processing and interpreting context, GPT can provide relevant suggestions or actions, ensuring smoother interactions between humans and machines. For example, an operator managing an industrial control system can receive tailored recommendations or alerts generated by a GPT-based system.
- Improving User Training and Support: GPT can act as a virtual assistant, guiding users through system processes, troubleshooting, and training in real time. This capability is particularly valuable in industries where workers must quickly adapt to new technologies.

By facilitating seamless interaction between humans and machines, GPT contributes to human-centered design and enhances productivity in industrial systems. This alignment with HCI demonstrates how interdisciplinary approaches can unlock new possibilities for industrial engineering.

2. Knowledge Management in Industrial Organizations

In industrial engineering, knowledge management is a cornerstone of innovation, process improvement, and workforce development. The ability to collect, organize, and disseminate knowledge efficiently is essential for maintaining a competitive edge in today’s industries. GPT-based systems excel in this area by leveraging their NLP capabilities to transform how knowledge is managed and shared.

GPT supports knowledge management by:

- Organizing Information: GPT can analyze vast amounts of unstructured data, such as technical documents, meeting transcripts, or research papers, and organize it into structured formats. This makes it easier for organizations to access and utilize critical information.
- Generating Training Materials: GPT can create customized training guides or tutorials tailored to the needs of specific teams or processes. This accelerates workforce development and ensures consistent knowledge transfer across the organization.
- Enhancing Collaboration: By providing clear summaries, translations, or interpretations of complex technical concepts, GPT bridges communication gaps between teams with diverse expertise. For instance, engineers, managers, and IT specialists can collaborate more effectively with the help of GPT-generated insights.

Through these applications, GPT transforms knowledge management from a time-consuming task into a streamlined process, driving innovation and improving operational efficiency.

Why Interdisciplinary Approaches Matter

Interdisciplinary collaboration is essential for addressing the complexities of modern industrial systems. As industrial engineering increasingly intersects with fields like computer science, organizational behavior, and technology management, tools like GPT become critical enablers of integration.

At Jurnal Optimasi Sistem Industri (JOSI), we prioritize research that bridges these disciplines, recognizing that the most impactful innovations often emerge at their intersection. GPT’s ability to connect and enhance multiple fields makes it an ideal subject for study and application within our focus areas.

How GPT Aligns with JOSI’s Vision

GPT-based systems resonate deeply with JOSI’s emphasis on interdisciplinary collaboration, particularly in fostering innovation at the nexus of engineering, technology, and organizational science. The journal actively supports research that leverages such technologies to:

- Improve system optimization.
- Foster collaboration across diverse fields.
- Align industrial practices with sustainable development goals, such as innovation (SDG 9) and quality education (SDG 4).

Research exploring the interdisciplinary applications of GPT not only advances industrial engineering but also contributes to a broader understanding of how AI can address complex, real-world challenges.

Generative Pre-trained Transformers (GPT) represent a paradigm shift in how interdisciplinary challenges are approached within industrial engineering. From improving human-computer interaction to revolutionizing knowledge management, GPT demonstrates its potential to bridge gaps between fields and drive meaningful innovation.

At Jurnal Optimasi Sistem Industri, we are excited to explore the interdisciplinary possibilities of GPT and other emerging technologies. If you are conducting research on the applications of GPT in industrial engineering, knowledge management, or HCI, we encourage you to submit your work to our journal. Together, let’s continue to advance the boundaries of interdisciplinary collaboration and system optimization.

Stay connected with us for more insights into the latest advancements at the intersection of AI and industrial systems!

This post is a part of the our discussion about Relevance of GPT in Industrial Engineering (https://doi.org/10.25077/josi.11122024)