Development Of Smart Products Research Articles

Innovation ecosystem for smart product: empirical quantification of its key dimensions in SMEs of 21 European countries

AbstractThis paper aims to quantify the innovation ecosystem model for allowing the development of smart products at the country level. In this regard, the research used an empirical approach to scale and validate the six dimensions of an innovation ecosystem model among the small and medium-sized enterprises of 21 European countries. The quantitative methods of panel data analysis and Pearson correlation tests between variables of the innovation ecosystem and smart products were considered to examine six research hypotheses. Three dimensions of the innovation ecosystem model, i.e., configuration, change, and capability, have enough effects to accelerate high levels of smart products in the small and medium-sized enterprises of European countries, supporting the external and internal economic partnerships of institutions and companies, cultural changes in functional status, and knowledge-based capabilities of technological skills in each ecosystem. In addition, hierarchical clustering analysis for the classification of the countries showed that some countries, e.g., the United Kingdom, Netherlands, Sweden, Switzerland, Germany, Denmark, France, and Norway, could support their powerful smart products for small and medium-sized enterprises at the national level due to their high mean innovation ecosystem values. Overall, the research can describe the managerial implications regarding the knowledge-based capabilities of the technological skills in each ecosystem to be utilized by managers and stakeholders in small and medium-sized enterprises.

Development of intelligent tools for logistics: practice and prospects of use

The article examines SMART products (SMARTtechnologies, SMART- systems, SMART-objects) used by logisticians in the process of carrying out logistics activities for business structures and others. It is noted that today, without SMART-products, logistics will lose its position as an effective tool that helps market players effectively conduct business and work effectively in the conditions of the development of globalization and internationalization of the market space. The purpose of the article is a thorough review and analysis of modern SMART-products, which are advisable to use in the field of logistics in order to rationally organize the logistics activities of enterprises, based on the formation of competitive supply chains. It was established that digitalization is currently one of the key factors of increasing value not only for individual enterprises and industries, but also for states. It is argued that the digital transformation marked the beginning of a new stage in the development of logistics - digital logistics based on the development of SMART-products: SMART-technologies, SMART-systems, SMART-objects. The main intelligent products are characterized, namely: Internet of Things, robotics and cyber systems, artificial intelligence, big data, paperless technologies, additive technologies (3D printing), cloud and fog computing, unmanned and mobile technologies, biometric technologies, quantum technologies, identification technologies, blockchain. It is noted that the listed products are constantly supplemented, in accordance with the development of IT technologies and means of communication between digital devices. It is substantiated that SMART -products are an important factor in the growth of sales volumes and obtaining significant profits from logistics activities. A thorough analysis of the suitability for use by logisticians in the practical activities of software products, which became the basis for the digitalization of transport, blockchain, big data (BIG DATA), uberization, was carried out; SMART technologies – 3D printing, sensor technologies (ST), GRID - technologies; SMART-objects - augmented reality (ar - augmented reality), smart products, drones, unmanned transport, robotics, as well as SMART-systems - cyber-physical systems (CPS) used in production (CYBER-PHYSICAL PRODUCTION SYSTEM (CPPS), intelligent systems and the Internet of Things (INTERNET OF THINGS). It has been proven that SMART -products today are able to ensure a high level of competitiveness of business entities in various sectors of the economy: wholesale and retail trade, agriculture, industry, health care, postal services, etc. Key words: logistics, intelligent logistics tools, logistics activity, digital transformation, logistics efficiency, logistics effectiveness, competitiveness.

Is AI testing beneficial for the manufacturer and social welfare? Optimal test strategy of a smart product

The rapid technological revolution of Industry 4.0 has set off rapid advancement in the smart product development. Testing the smart product’s system before release to market is crucial for ensuring proper functioning. Smart product manufacturers must carefully consider different testing modes to choose the optimal one based on product characteristics and consumer’s shopping intention. Additionally, different testing modes have varying impacts on the environment and social welfare, as well as profitability of the product. This study utilizes a two-period game theory model to analyze a smart product manufacturer’s optimal testing mode and pricing decision. Three testing mode are evaluated: manual testing mode (MT mode), artificial intelligence testing mode (AT mode), and public testing mode (PT mode). Consumers’ utility is influenced by factors such as consumer preferences, product quality, usage duration, and network externality effect. Our findings indicate that the optimal testing mode depends on quality improvement and network effect coefficients. Specifically, when the degree of quality improvement is high and the network effect is moderate, MT mode is preferred; when the quality improvement is high but the network effect is small, AT mode dominates; under other conditions, PT mode is optimal. Quality improvement and network effect coefficients have similar effects on pricing decisions but impact the profits in different manners. Social welfare is the highest under MT mode when the network effect is high and quality improvement is low, under AT mode when network effect is low and quality improvement is high, and under PT mode when both factors are high or low. Finally we provide a numerical example of how profit-driven business decisions may conflict with social welfare, potentially leading to lower social welfare than the theoretical optimum under the chosen testing mode strategy.

Strategies for development of smart and green products using Blockchain-IoT integrated architecture

Strategies for development of smart and green products using Blockchain-IoT integrated architecture

Quality 4.0 in Digital Manufacturing – Example of Good Practice

Purpose: The ever-evolving market dynamics and the trend toward increased product individualization demand a high degree of adaptability in production management. This calls for novel approaches, such as Industry 4.0 (I4.0), which integrates the Quality 4.0 (Q4.0) model as well. Methodology/Approach: I4.0 builds upon the foundation of digital manufacturing and entails three key dimensions: (i) The employment of advanced digital technologies to enable digital production, (ii) The development of smart products, which incorporate novel production methods and innovative features, and, (iii) The adoption of an intelligent supply chain, designed to facilitate the procurement of raw materials and the delivery of finished goods. In our research studies, we focus specifically on the first and third approaches. Findings: A bilateral flow of information in collaborative manufacturing is facilitated through digital platforms that span the entirety of the production process, from the inception of cutting-edge product designs to the final delivery to end-customers, integrating quality management (QM) as well. Research Limitation/Implication: The current study outlines a QM model developed for a digital factory in Serbia, utilizing the Q4.0 model, with particular emphasis on the workshop section, integrated within the Enterprise Resource Planning/Manufacturing Execution Systems module. Originality/Value of paper: The manuscript serves as a notable illustration of best practices for digital manufacturing, and the implementation of a digital QM model within the metalworking industry.

Prototyping in smart product design: Investigating prototyping tools to support communication in the early stage smart product development

ABSTRACT Smart product design (SPD) is more complex than traditional product design (TPD), requiring intense interdisciplinary collaboration. It is well understood that prototypes are an effective means to facilitate communicating design concepts. However, there is limited research concerning prototyping preferences of design disciplines involved in SPD. The research explores the use of prototyping in smart product development. Specifically, it aims to understand the preferences and dimensions of fidelity of different prototyping tools that can support communication in the SPD process for various stakeholders. This paper presents two surveys. The first investigates the use of prototyping tools by different disciplines involved in SPD versus TPD. The second compares elements of key prototyping tools used across disciplines within SPD. Results show that the interactivity and environment dimensions of fidelity of prototyping tools motivate differences in preference between SPD and TPD. Moreover, user depiction and contextual information are key elements of prototyping that support designers in communicating interactive and environmental qualities of SPD concepts.

Research on the Factors Affecting the Adoption of Smart Aged-Care Products by the Aged in China: Extension Based on UTAUT Model.

With the rapid development of network technology and smart technology, smart aged-care products are becoming increasingly valued for their ability to help the aged actively cope with the challenges of aging. However, seniors face challenges in using smart aged-care products for many reasons, which reduces their willingness to adopt them. As a result, the sustainable development of smart aged-care products is constrained. This study combined the unified theory of technology acceptance and use, perceived risk theory and perceived cost theory, and reconstructed a research model that investigated the adoption of smart aged-care products by the elderly in China. Questionnaires were given to older Chinese adults in this study, and 386 valuable responses were received. The findings of the structural equation model (SEM) analysis are as follows: (1) performance expectancy, effort expectancy, and social influence were positively related to the behavioral intention of seniors to use smart aged-care products; (2) perceived cost and perceived risk were negatively related to the behavioral intention of seniors to use smart aged-care products; (3) perceived risk indirectly affected use behavior through behavioral intentions; (4) facilitating conditions did not have a significant impact on the use behavior of seniors in adopting smart aged-care products. Based on the empirical results, this study sought to improve the use behavior of the aged in relation to the adoption of smart aged-care products, and provided suggestions to improve the overall service quality and sustainability of those products.

An Extended AI-Experience: Industry 5.0 in Creative Product Innovation.

Creativity plays a significant role in competitive product ideation. With the increasing emergence of Virtual Reality (VR) and Artificial Intelligence (AI) technologies, the link between such technologies and product ideation is explored in this research to assist and augment creative scenarios in the engineering field. A bibliographic analysis is performed to review relevant fields and their relationships. This is followed by a review of current challenges in group ideation and state-of-the-art technologies with the aim of addressing them in this study. This knowledge is applied to the transformation of current ideation scenarios into a virtual environment using AI. The aim is to augment designers' creative experiences, a core value of Industry 5.0 that focuses on human-centricity, social and ecological benefits. For the first time, this research reclaims brainstorming as a challenging and inspiring activity where participants are fully engaged through a combination of AI and VR technologies. This activity is enhanced through three key areas: facilitation, stimulation, and immersion. These areas are integrated through intelligent team moderation, enhanced communication techniques, and access to multi-sensory stimuli during the collaborative creative process, therefore providing a platform for future research into Industry 5.0 and smart product development.

Customer involvement in technological development of smart products: empirical evidence from a coffee-machine producer

PurposeThis paper aims to explore how customer involvement unfolds in the development of a smart product. Smart product development poses new challenges to firms. In particular, the buyers’ and users’ involvement has shown novel dynamics in smart product development. These peculiarities are linked with the specific characteristics of the digital technology embedded into the smart products. This study’s rationale is to analyse the frictions arising from potential divergent objectives between the focal firm and its customers when digital technologies are embedded in traditional products.Design/methodology/approachThis study adopted an explorative and qualitative approach to investigate new emerging dynamics of customer involvement during technological development. A coffee machine producer is selected as a case study to uncover new insights and a novel perspective on the phenomenon of customer involvement in smart product development. Data analysis followed an abductive approach that allowed to identify the dimensions of friction emerging during the technological development process.FindingsThe case study analysis depicts that smart product development presents novel customer involvement dynamics. In particular, this study abductively identifies dimensions of friction emerging between the focal firm and buyers/users. Friction arises in the technological interface between the actors involved. These dimensions of friction address the complexities of developing technology in terms of smart products with customer involvement. This study suggests that embedding of technology into an existing product might change how customers are involved.Originality/valueEven though customer involvement in product innovation has been extensively studied in management literature, this paper focused on a new type of innovation, smart products. To the best of the authors’ knowledge, no previous studies have yet empirically explored customers’ involvement while embedding digital technologies into existing products to create smart products. In particular, this study sheds light on the dimensions of friction emerging between the focal firm and the actors of the business network. This study unfolds novel contributions to the Industrial Marketing and Purchasing literature on technological development.

Knowledge Collaboration Approach in Smart Product Innovation Networks

Due to the transformation of traditional domain specific products to smart, connected and interdisciplinary products that are increasingly developed within value creation networks, an exchange of innovation-relevant knowledge in early engineering phases is required, covering interdependencies of several technical systems. Knowledge-based collaboration within a value creation network could enable an acceleration during the innovation development of smart products. Discipline- and stakeholder-specific knowledge, e.g. semiconductor research and production knowledge along the product lifecycle must be prepared for the usage within innovation development. This paper introduces a conceptual approach of a knowledge base to support the collaboration during innovation processes within value creation networks for smart products. The main focus is the sharing of relevant knowledge from different stakeholders within the innovation value creation network. Through knowledge networking, decentrally collected initial knowledge is centralized, made explorable and realized through a three-stage tagging architecture similar to an ontology. The collaboration of different stakeholders is enabled through mutual knowledge interests and automated suggestions independent from their respective IT ecosystems. The presented approach is instantiated and validated by considering the function to charge mobile phones wirelessly while car driving. Prerequisites for the presented approach are discussed.

Overview of smart masks and research on new technology

<p>The smart mask is a new type of mask with active air supply and breathing. It adopts an external electric fan-forced air supply system, which can effectively reduce the user’s breathing load and achieve the purpose of improving comfort and user experience. However, in the current market, the function of smart masks is relatively simple with weak practicability and limited application. Based on these situations and in the research of a large number of smart masks and other types of masks, their application scenarios, advantages and disadvantages of the current technologies used in smart masks are analysed and compared to demonstrate their advantages in comfort and functionality. In terms of application prospects, new technologies can be integrated into the research and development of smart masks, providing new ideas for the research and development of new masks, which is crucial to the future market development of smart wearable products.</p>

Implementing Industry 4.0 in Australia: Insights from Advanced Australian Manufacturers

This study explores Industry 4.0 in the Australian context, where manufacturing is dominated by smaller firms servicing the domestic market. We interviewed 20 advanced Australian manufacturers from diverse fields, capturing detailed descriptions of the Industry 4.0 implementation process. We compared the themes that emerged from their descriptions with the factors typically assessed in Industry 4.0 frameworks to draw out differences in emphasis. Consistent with these frameworks, Australian manufacturers were focused on using Industry 4.0 technologies to automate the capture, integration and analysis of data. To enable this activity, they were reorganising workforce roles and developing new skill sets. Knowledge sharing and collaborations within and across the organisation were seen to be especially important for small Australian manufacturers (with limited funding for technology investment and research and development) to maintain global competitiveness. However, while most Industry 4.0 frameworks describe supply chain applications, the development of smart products and services, and the need to adopt a strategy-led approach, relatively few participants spoke about these opportunities. Even fewer addressed the need for improved governance, standards and data security in the context of Industry 4.0. We argue that these gaps are best addressed through government policy and investment focusing beyond manufacturers, to support Industry 4.0 uplift across key domestic supply chains.

Supporting Collaborative Innovation Processes in Smart Product Value Creation Networks

The development of smart products and systems includes a dramatically growing share of non-mechanical domains like microelectronic and software. This determines fundamentally new collaboration challenges and needs for system and product developers and their industrial organizations. Besides the rising number of relevant engineering disciplines (e.g. product-related internet-based service engineering and data platform engineering), the collaboration across several disciplines needs to become more systematic and has to be based on consistent system models. Since traditional value chains are transforming into new agile and distributed value creation networks, engineering collaboration approaches and solutions also have to stronger emphasize model-based, cross-company engineering collaboration. Also, the number of engineering stakeholders involved is increasing, while at the same time stakeholders are taking on new roles and completely new players are emerging, the collaboration share also has to grow continuously. This paper introduces a generic methodical approach for modeling collaborative innovation processes in value creation networks for smart products and supporting them with information technology by using an integrated, cross-company knowledge base. The support of engineering collaboration with a generic common reference innovation process along the value creation network with a seamless transformation into the engineering phase, are part of the focused approach goals. This generic approach has been instantiated according to the specific needs of early innovation phases in the field of automotive microelectronic integration considering the whole value creation network.

A Fuzzy Logic Recommendation System to Support the Design of Cloud-Edge Data Analysis in Cyber-Physical Systems

The ongoing 4th industrial revolution is characterized by the digitization of industrial environments, mainly based on the use of Internet of Things, Cloud Computing and Artificial Intelligence (AI). Regarding AI, although data analysis has shown to be a key enabler of industrial Cyber-Physical Systems (CPS) in the development of smart machines and products, the traditional Cloud-centric solutions are not suitable to attend the data and time-sensitive requirements. Complementary to Cloud, Edge Computing has been adopted to enable the data processing capabilities at or close to the physical components. However, defining which data analysis tasks should be deployed on Cloud and Edge computational layers is not straightforward. This work proposes a framework to guide engineers during the design phase to determine the best way to distribute the data analysis capabilities among computational layers, contributing for a lesser ad-hoc design of distributed data analysis in industrial CPS. Besides defining the guidelines to identify the data analysis requirements, the core contribution relies on a Fuzzy Logic recommendation system for suggesting the most suitable layer to deploy a given data analysis task. The proposed approach is validated in a smart machine testbed that requires the implementation of different data analysis tasks for its operation.

Printed and flexible electronics in smart textiles for different industrial sectors

Since 2006, Portuguese CeNTI – Centre for Nanotechnology and Smart Materials – has been involved in a wide number of research & innovation projects in the field of smart textiles, supporting several industrial partners from different application sectors in the development of smart textile-based products with high added value

Research Hotspot and Trend Analysis of China’s Elderlyoriented Smart Products

The Chinese government attaches great importance to the current situation of population aging, so it has introduced relevant aging policies. The combination of new technologies has played a positive role in the development of Elderly-oriented smart products of enterprises. Based on the research literature on Elderly-oriented smart products collected in CNKI database in recent ten years (2012-2022), this paper makes a quantitative analysis on the research results of Elderly-oriented smart products in China with the help of CiteSpace visual analysis software. Through research hotspots and evolution trends, it is found that the theme can be extended: the upgrading and construction of Elderly-oriented smart products will be a hot research topic in the academic community in the future.

Methodology for an automatic and early manufacturing technology selection on a component level

Production systems of the automotive industry process parts that were previously designed and manufactured according to different manufacturing technologies. In car body architectures, additive manufacturing (AM) has become a relevant technology for supplementing conventional manufacturing technologies, e.g., casting or forming technologies. This paper presents a methodology for an automatic and objective early-stage analysis of part features and the subsequent identification of the parts’ most suitable manufacturing technology. For this purpose, a comprehensive database is required, in which several technological and economic parameters need to be derived and predicted, including part requirements, production inherences, expected lifecycle costs, as well as geometric information. Based on this, data screening allows to effectively evaluate the technological and economic potential for a component to be manufactured either conventionally or additively in early product development phases. One core element is the part requirements derivation and analysis within one novel module of the part screening methodology. Subsequently, the product development process and the production system can be adapted according to the identified, most promising manufacturing technologies. Hence, this early-stage decision allows for cost reduction through an increased planning reliability. This work thus contributes to a successful co-evolution of smart product development and the production processes.

A survey of immersive technologies and applications for industrial product development

With the expanded digitalization of manufacturing and product development process, research into the use of immersive technology in smart manufacturing has increased. The use of immersive technology is theorized to increase the productivity of all steps in the product development process, from the start of the concept generation phase to assembling the final product. Many aspects of immersive technology are considered, including techniques for CAD model conversion and rendering, types of VR/AR displays, interaction modalities, as well as its integration with different areas of product development. The purpose of this survey paper is to investigate the potential applications of immersive technology and advantages and potential drawbacks that should be considered when integrating the technology into the workplace. The potential application is broad, and the possibilities are continuing to expand as the technology used becomes more advanced and more affordable for commercial business to implement on a large scale. The technology is currently being utilized in the concept generation and in the design or engineering of new products. Additionally, the immersive technology have great potential to increase the productivity of assembly line workers and of the factory layout/functionality, and could provide a more hands-on form of training, which leads to the conclusion that immersive technology is the step to the future in terms of smart product development strategies to implement for employers.

Research on the Evaluation of Customer requirement Importance of Smart Products Based on Online Comments and Improved Quantitative Kano Model

With the development and popularization of smart products, the technological differences of products are decreasing, and the phenomenon of product homogeneity is becoming more and more obvious. It is necessary for the smart product manufacturing firms have the capability to analyze customer requirement deeply and adapt to the dynamically changing market quickly. Therefore, the traditional technology-oriented product development model is no longer suitable for manufacturers to obtain a competitive advantage. Based on this, this paper proposed a method to evaluate the importance of customer demands based on online comments and quantitative Kano model. First, the Python crawler tool is used to obtain online customer reviews of relevant products and the word segmentation processing is performed to obtain the product features and frequency that customers are mainly concerned about, and then the initial importance of demand can be calculated. Furthermore, use the quantitative Kano model to determine the customer satisfaction and revise the initial importance of the requirements to obtain a more reasonable ranking of the importance of user needs. Finally, a case study is carried out with the smart bracelet as an example to verify the effectiveness and feasibility of the model proposed in this paper.

Beaming market simulation to the future by combining agent-based modeling with scenario analysis

Agent-based simulation has become an established method for innovation and technology diffusion research. It extends traditional approaches by modeling diffusion processes from a micro-level perspective, which enables the consideration of various heterogeneous stakeholders and their diverse interactions. While such a simulation is well suited to capture the complex behavior of markets, its application is challenging when it comes to modeling future markets. Therefore, we propose a multi-method approach that combines scenario analysis that generates multiple “pictures of the future” with an agent-based market simulation that offers insight into the potential outcomes of today’s strategic (technological) decisions in each of these futures. Thus, simulation results can provide valuable decision support for corporate planners and industrial engineers when they are engaged in technology planning. This paper describes the novel approach and illustrates it through a sample application that is based on an industry-related research project on the development and market introduction of smart products.