Generative Product Design Processes: Humans and Machines Towards a Symbiotic Balance

Tufarelli, Margherita; Cianfanelli, Elisabetta

doi:10.1017/pds.2022.181

Cited by 2 publications

(1 citation statement)

References 17 publications

(13 reference statements)

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“…This indicates that between humans and machines still visible patterns of conversation settings exist. The conversation process is already set up with algorithms that provide solutions and improvements in terms of efficiency (Tufarelli & Cianfanelli, 2022).…”

Section: Discussionmentioning

confidence: 99%

Communication Styles of Human-Machine Interaction in the ChatGPT

Ningsih,

Rohmah

2024

IJEFL

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This research aims to analyze the communication style of Human-machine interaction based on ChatGPT 3.5 to understand the pros and cons, as well as potential improvements in the implementation of this technology. Humans have limitations in processing complex information. The emergence of machines helps humans complete work, and many machine features provide solutions. This research found out human-machine interaction, focuses on communication and using cooperative principles that have four maxims: maxim quantity, maxim quality, maxim relation, and maxim manner are some of the divisions that will be sought in human-machine interaction. The research uses a qualitative method by using a chatbot as a GPT version 3.5 chat that is then given a command. Then, the data is collected and analyzed. From this analysis, human-machine interaction qualitatively has good performance but has a deficiency in maximum quantity due to too much information given. The outcome of the violation of the maxim quantity that stands out requires self-interpretation where the statements correspond to the question. This research is expected to help develop human-machine interaction technology primarily in business.

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Section: Discussionmentioning

confidence: 99%

Communication Styles of Human-Machine Interaction in the ChatGPT

Ningsih,

Rohmah

2024

IJEFL

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A Brief Review of Computational Product Design: A Brand Identity Approach

2023

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On the way to designing customized products as one of the core activities of Industry 4.0, the strategy of computational design emerges as a unique design process due to its flexibility and simplicity. More specifically, the aforementioned strategy is concerned with the study of brand identity and its description in the development of commercial industrial products. The proposed design approach is focused on the study of branded product forms following computational design methodologies, i.e., employing textual or/and visual programming languages. The paper presents an overview of in-depth research studies which deal with the systematic way of creation, evolution, and transformation of industrial products with modern digital tools. Through the review, 100 studies have been analyzed over the last 15 years. The background of this research includes definitions from the specific four pillars of the modern theory of industrial design, e.g., product design, digital design, visual representation, and product identity. Furthermore, the current paper combines the use of computational design with specific parameters of visual brand elements in order to develop a methodological tool for the mass customization of industrial products. Moreover, the proposed framework offers a great deal of flexibility in both design and manufacturing, while many design alternatives could become available in a very short time. Finally, the impact of this paper is the correlation between computational design techniques and the theoretical background of brand identity principles (i.e., shapes, geometries, styles, textures, colors, and materials) for inspiring novel ideas among engineers, designers, and marketers.

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Generative Product Design Processes: Humans and Machines Towards a Symbiotic Balance

Cited by 2 publications

References 17 publications

Communication Styles of Human-Machine Interaction in the ChatGPT

Communication Styles of Human-Machine Interaction in the ChatGPT

A Brief Review of Computational Product Design: A Brand Identity Approach

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