scholarly journals Systemic Functions Evaluation based Technological Innovation System for the Sustainability of IoT in the Manufacturing Industry

2019 ◽  
Vol 11 (8) ◽  
pp. 2342 ◽  
Author(s):  
Kao ◽  
Nawata ◽  
Huang
Keyword(s):  
Decision Making ◽  
Technological Innovation ◽  
Manufacturing Industry ◽  
Innovation System ◽  
Government Procurement ◽  
Smart Manufacturing ◽  
Technological Innovations ◽  
Industrial Competitiveness ◽  
Industrial Sustainability ◽  
Study Results

Technological innovations are regarded as the tools that can stimulate economic growth and the sustainable development of technology. In recent years, as technologies based on the internet of things (IoT) have rapidly developed, a number of applications based on IoT innovations have emerged and have been widely adopted by various public and private sectors. Applications of IoT in the manufacturing industry, such as manufacturing intelligence, not only play a significant role in the enhancement of industrial competitiveness and sustainability, but also influence the diffusion of innovative applications that are based on IoT innovations. It is crucial for policy makers to understand these potential reasons for stimulating IoT industrial sustainability, as they can facilitate industrial competitiveness and technological innovations using supportive means, such as government procurement and financial incentives. Therefore, there is a need to ascertain different factors that may affect IoT industrial sustainability and further explore the relationship between these factors. However, finding a set of factors that affects IoT industrial sustainability is not easy. Recently, the robustness of a theoretical framework, termed the technological innovation system (TIS), has been verified and has been used to explore and analyze technological and industrial development. Thus, it is suitable for this research to use this theoretical model. In order to find out appropriate factors and accurately analyze the causality among factors that influence IoT industrial sustainability, this research presents a Bayesian rough Multiple Criteria Decision Making (MCDM) model based on TIS functions by integrating random forest (RF), decision making trial and evaluation (DEMATEL), Bayesian theory, and rough interval numbers. The proposed analytical framework is validated by an empirical case of defining the causality between TIS functions to enable the industrial sustainability of IoT in the Taiwanese smart manufacturing industry. Based on the empirical study results, the cause group consists of entrepreneurial activities, knowledge development, market formation, and resource mobilization. The effect group is composed of knowledge diffusion through networks’ guidance of the search, and creation of legitimacy. Moreover, the analytical results also provide several policy suggestions promoting IoT industrial sustainability that can serve as the basis for defining innovation policy tools for Taiwan and late coming economies.

scholarly journals Problems of Decision-Making in Implementation of Technological Innovations in Transport Industry

2022 ◽  
Vol 19 (4) ◽  
pp. 92-101
Author(s):  
E. O. Koshcheeva ◽  
S. Yu. Lyapina
Keyword(s):  
Decision Making ◽  
Technological Innovation ◽  
Technological Innovations ◽  
Economic Factors ◽  
Special Role ◽  
Strategic Decisions ◽  
Logistics Industry ◽  
Technological Paradigm ◽  
Transport Industry ◽  
Transport Complex

The article considers the features of transport as an object of technological innovation, due, on the one hand, to the service nature of the main activity and the specifics of innovative processes during provision of transport and logistics services, and, on the other hand, to the high capital intensity and technological complexity of the infrastructure transport complex, which is the focus point of technological innovation.The objective of the article is to substantiate the initial prerequisites for developing an alternative approach to making strategic decisions on development of transport organisations based on technological innovations, which, besides the traditional justification of economic efficiency, considers several non-economic factors. The method of substantiation is a systemic strategic analysis, which allows to study the features of the transport complex in the context of the factors of external environment and their dynamics.Regarding the Russian Federation, the scale of the national territory, natural and climatic diversity and uneven territorial distribution of the resource and production base determine the special role and place of transport in the national economy, which quite often leads to the need to make decisions on development of the transport complex based on predominantly non-economic factors (such as security, reliability, environmental friendliness, etc.) and on scientific, technical, political and socio-economic forecasts. At the same time, private enterprises (with or without participation of the state) dominate currently almost all transport sectors where they operate on the principles of profitability, investment attractiveness and competitiveness, which leads to inconsistency of internal decision-making criteria in the field of technological strategies.The ongoing change in the technological paradigm is an additional and significant factor determining trends in transport developments. It is based on the processes of digitalisation and digital transformation of the transport and logistics business. The problems of decision-making in implementation of technological innovations in transport industry, arising from its peculiarities, necessitate a revision of approaches since economic assessments of efficiency are not always able to reflect the real needs and feasibility of choosing mainstream trends in technological development of the transport system.The analysis of the features of the transport and logistics industry based on universal experience and cases in Russian practices in the context of formation of a new technological paradigm makes it possible to substantiate the methodology for making strategic decisions on implementation of technological innovations. 

scholarly journals How Technological Innovation Affect China’s Pharmaceutical Smart Manufacturing Industrial Upgrading

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Su Wang ◽  
Yuwen Chen
Keyword(s):  
Technological Innovation ◽  
Manufacturing Industry ◽  
New Technologies ◽  
Digital Transformation ◽  
Pharmaceutical Manufacturing ◽  
Smart Manufacturing ◽  
Manufacturing Companies ◽  
Industrial Upgrading ◽  
Depth Analysis ◽  
Innovative Resources

In recent years, a new generation of information technology has provided sufficient technical support for the smart manufacturing industry. In order to promote the upgrading of China’s pharmaceutical smart manufacturing industry, the direction of industrial upgrading and transformation will be discussed from the perspective of technological innovation. According to the input and output data of technological innovation in China’s pharmaceutical manufacturing industry from 2007 to 2019, the DEA method is used to analyze the allocation of innovative resources in China’s pharmaceutical manufacturing industry in recent years. The study found that the efficiency of technological innovation in China’s pharmaceutical manufacturing industry fluctuated greatly from 2007 to 2019, with a low overall level and varying degrees of wasted resources. On this basis, an in-depth analysis of the system architecture of the pharmaceutical smart manufacturing industry under the Industry 4.0 environment was performed. Finally, four paths for the digital transformation of China’s pharmaceutical manufacturing industry are proposed. Chinese pharmaceutical manufacturing companies need to use new technologies to carry out comprehensive intelligent upgrading and digital transformation to improve innovation efficiency.

scholarly journals Analysis of the technological impact on industry and its effects on waste production and disposal: a case study of the surfboard manufacturing industry

2018 ◽  
Vol 40 ◽  
pp. 49
Author(s):  
Ricardo Luis Barcelos ◽  
Rachel Faverzani Magnago ◽  
Alexandre Avila Leripio
Keyword(s):  
Technological Innovation ◽  
Manufacturing Industry ◽  
Manufacturing Industries ◽  
Numerical Control ◽  
Technological Innovations ◽  
Production Chain ◽  
Waste Production ◽  
Production Stages ◽  
Technological Impact

Cleaner Production (CP) advocates the application of preventive and integrated  strategies to processes products minimizing the generation of waste and pollution. However, not always technological innovations in production bring with it an improvement for CP. The surfboard industry has been dismissive of CP. Studies revealed a concentration of the production residues on the manufacturers due to the vertical process of the production stages. Nonetheless, the incorporation of machining technology of the polyurethane blocks through Computerized Numerical Control (CNC) led to a horizontal process. The aim of this study was to map the current process, identifying the major waste producers, and detailing management for these wastes. A case study was carried out to examine the surfboard  industry. The survey revealed that the links of the production chain can be accomplished by the diverse actors participating in the manufacturing industry. However, the largest amount of waste is produced by big manufacturing industries rather than small, outsourced companies. It became clear that the introduction of CNC technology was responsible for the centralization of waste production, previously distributed among all manufacturers. Technological innovation had no impact on the reduction or reuse of waste or even a better management of its disposal.

scholarly journals Comportamiento métrico de las patentes concedidas en Cuba: su contribución a la innovación tecnológica nacional

2018 ◽  
pp. 271
Author(s):  
Maidelyn Díaz Pérez ◽  
Raudel Giráldez Reyes ◽  
Humberto Andrés Carrillo-Calvet
Keyword(s):  
Social Networking ◽  
Technological Innovation ◽  
International Organizations ◽  
Innovation System ◽  
Technological Innovations ◽  
Redes Sociales ◽  
Industrial Property ◽  
National Science ◽  
Technological Developments ◽  
Visualization Of Data

Los estudios métricos de patentes desde finales del pasado xx son una valiosa herramienta de vigilancia científica tecnológica y de innovación, convirtiéndose en instrumento indispensable para conocer el comportamiento tecnológico internacional. Sin embargo, los estudios patentométricos no son aplicados óptimamente por todos los países, ni por todos los organismos internacionales, tampoco son aprovechadas todas las potencialidades que ofrecen estos estudios para conocer los diferentes contextos de las innovaciones tecnológicas de un país. Este artículo tiene como objetivo analizar el comportamiento métrico de las patentes concedidas en Cuba, aplicando una metodo logía propia que describe las principales innovaciones científico-tecnológicas patentadas por la Oficina Cubana de Propiedad Industrial. La metodología propuesta utiliza el software proIntec para la descarga, normalización, procesamiento, análisis y visualización de los datos procedentes de las patentes, y se aplica un amplio grupo de indicadores métricos relacionales y complejos, así como técnicas de redes sociales para visualizar los principales comportamientos de las innovaciones tecnológicas cubanas. Los resultados finales manifiestan las potencialidades de los estudios métricos de patentes, al poder representar los desarrollos tecnológicos del país y sus contribuciones al sistema de ciencia e innovación tecnológica nacional.AbstractMetric patent studies since the end of the last century are a valuable tool for scientific technological and innovation surveillance, becoming an indispensable instrument for knowing the international technological behavior. However, patentometric studies are not applied optimally by all countries or by all international organizations, nor are all the potential of these studies used to know the different contexts of a country’s technological innovations. This research aims to analyze the metric behavior of patents granted in Cuba applying an own methodology that describes the main technological scientific innovations patented by the Cuban Office of Industrial Property. The proposed methodology uses proIntec software for the download, normalization, processing, analysis and visualization of data from patents, and applies a large group of relational and complex metrics, as well as social networking techniques to visualize the main behaviors of Cuban technological innovations. The final results show the potential of metric patent studies to represent the country’s technological developments and its contributions to the national science and technological innovation system.

A Literature Review of Design Decision Making in Disruptive Technological Innovations of New Products

2020 ◽  
Author(s):  
Mikhail Y. Nikolaev ◽  
Clement Fortin
Keyword(s):  
Decision Making ◽  
Product Development ◽  
Technological Innovation ◽  
Systems Engineering ◽  
Technological Innovations ◽  
Decision Making Process ◽  
Design Decision ◽  
Development Phase ◽  
Disruptive Innovations ◽  
Lifecycle Design

Abstract This paper reviews the information available on specifics of the design decision-making process for the case of disruptive technological innovations associated with new products and systems. It defines the term “disruptive technological innovation,” provides with the explanation of decision-making methodology peculiarities for this type of innovation, and describes currently existing techniques and tools to support design decision making in case of disruptive technological innovations. The current paper relates to decision making in systems engineering and design, and therefore deals with the design decision making. The terms “disruptive technologies” and “disruptive innovations” appeared at the end of the 1990s. Researchers frequently mention disruptive innovations and technologies in the description of technical products for different industries: aircraft, automotive, food, petroleum, etc. A disruptive technological innovation is defined as a combination of disruptive technology and disruptive innovation. A new product can be relatively a simple device like an unmanned aerial vehicle and a smartphone, or a complex system like a modern aerospace vehicle or a space information network. Being an innovative developed product, it possesses peculiarities influencing the product development phase of the product lifecycle design decision-making process and accompanying supporting techniques and tools. This review investigates the specifics of design decision making of disruptive technologically innovative products that influence different stages of the product development phase in their product lifecycles. The paper combines aspects of systems engineering with innovation theory, key elements of the design of complex systems, and highlights the product development phase of the product lifecycle design decision-making process.

scholarly journals Evaluating the Performance of Systemic Innovation Problems of the IoT in Manufacturing Industries by Novel MCDM Methods

2019 ◽  
Vol 11 (18) ◽  
pp. 4970 ◽  
Author(s):  
Kao ◽  
Nawata ◽  
Huang
Keyword(s):  
Empirical Study ◽  
Technological Innovation ◽  
Manufacturing Industry ◽  
Innovation Policy ◽  
Interdisciplinary Collaboration ◽  
Evaluation Model ◽  
Policy Instruments ◽  
Smart Manufacturing ◽  
Systemic Innovation ◽  
Entrepreneurial Activities

The Internet of Things (IoT) is an important technological innovation that can enhance industrial competitiveness and sustainability. Thus, governments need to carefully construct an innovation portfolio that promotes sustainable IoT development. To help define an accurate innovation policy and promote development of the IoT industries, potential problems in terms of systemic perspectives should be examined. Such problems, so-called “systemic innovation problems”, influence and block sustainable development of IoT technology as well as the IoT industry. However, past studies that explored systemic innovation problems in IoT-related industries are limited. Thus, this research aims to explore systemic innovation problems related to configuring an IoT innovation policy portfolio. A hybrid Bayesian rough based evaluation model was used to derive the most feasible policy instruments. The modified Delphi, Bayesian Rough Decision-Making Trial and Evaluation Laboratory Based Network Procedures (BR-DNP), and the modified Bayesian rough Vlse Kriterijumska Optimizacija I Kompromisno Resenje (MBR-VIKOR) were introduced. Gaps in performance corresponding to each systemic innovation problem can thus be assessed based on the features of technological innovation systems. The applicability of the proposed model for promoting industrial sustainability of IoT in the Taiwanese smart manufacturing industry (based on the opinions provided by Taiwanese experts) was verified by an empirical study. Eleven systemic innovation problems that influence the development of the IoT for the smart manufacturing industry were compared and ranked. Based on the results of the empirical study, the performance-gap ratio of “low level of interdisciplinary collaboration” problem is the lowest, as compared to other systemic innovation problems. In addition, the systemic functions of entrepreneurial activities and knowledge development are relatively more important than other systemic functions. The empirical results can serve as a basis for planning an IoT innovation policy portfolio definition and roadmap. Moreover, suggestions for enhancing current systemic innovation problems are provided for policy makers and industrial researchers, according to the results of the evaluation.

A Highly Efficient and Optimised Simulation Based Multi objective Decision-Making for FMS Control

2018 ◽  
Vol 6 (6) ◽  
pp. 98
Author(s):  
Shreyanshu Parhi ◽  
S. C. Srivastava
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Manufacturing Industry ◽  
Simulation Software ◽  
Shop Floor ◽  
Simulation Tool ◽  
Routing Flexibility ◽  
Decision System ◽  
Multi Objective ◽  
Arena Simulation

Optimized and efficient decision-making systems is the burning topic of research in modern manufacturing industry. The aforesaid statement is validated by the fact that the limitations of traditional decision-making system compresses the length and breadth of multi-objective decision-system application in FMS.  The bright area of FMS with more complexity in control and reduced simpler configuration plays a vital role in decision-making domain. The decision-making process consists of various activities such as collection of data from shop floor; appealing the decision-making activity; evaluation of alternatives and finally execution of best decisions. While studying and identifying a suitable decision-making approach the key critical factors such as decision automation levels, routing flexibility levels and control strategies are also considered. This paper investigates the cordial relation between the system ideality and process response time with various prospective of decision-making approaches responsible for shop-floor control of FMS. These cases are implemented to a real-time FMS problem and it is solved using ARENA simulation tool. ARENA is a simulation software that is used to calculate the industrial problems by creating a virtual shop floor environment. This proposed topology is being validated in real time solution of FMS problems with and without implementation of decision system in ARENA simulation tool. The real-time FMS problem is considered under the case of full routing flexibility. Finally, the comparative analysis of the results is done graphically and conclusion is drawn.

Artificial Intelligence as a Technological Innovation to Accelerate Economic Development

2019 ◽  
Vol 12 (3) ◽  
pp. 125-133
Author(s):  
S. V. Shchurina ◽  
A. S. Danilov
Keyword(s):  
Artificial Intelligence ◽  
Economic Development ◽  
Technological Innovation ◽  
Manufacturing Industry ◽  
New Technologies ◽  
Retail Trade ◽  
High Tech ◽  
Industrial Complex ◽  
Technological Gap ◽  
The Government

The subject of the research is the introduction of artificial intelligence as a technological innovation into the Russian economic development. The relevance of the problem is due to the fact that the Russian market of artificial intelligence is still in the infancy and the necessity to bridge the current technological gap between Russia and the leading economies of the world is coming to the forefront. The financial sector, the manufacturing industry and the retail trade are the drivers of the artificial intelligence development. However, company managers in Russia are not prepared for the practical application of expensive artificial intelligence technologies. Under these circumstances, the challenge is to develop measures to support high-tech projects of small and medium-sized businesses, given that the technological innovation considered can accelerate the development of the Russian economy in the energy sector fully or partially controlled by the government as well as in the military-industrial complex and the judicial system.The purposes of the research were to examine the current state of technological innovations in the field of artificial intelligence in the leading countries and Russia and develop proposals for improving the AI application in the Russian practices.The paper concludes that the artificial intelligence is a breakthrough technology with a great application potential. Active promotion of the artificial intelligence in companies significantly increases their efficiency, competitiveness, develops industry markets, stimulates introduction of new technologies, improves product quality and scales up manufacturing. In general, the artificial intelligence gives a new impetus to the development of Russia and facilitates its entry into the five largest world’s economies.

scholarly journals Data-Driven Dispatching Rules Mining and Real-Time Decision-Making Methodology in Intelligent Manufacturing Shop Floor with Uncertainty

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4836
Author(s):  
Liping Zhang ◽  
Yifan Hu ◽  
Qiuhua Tang ◽  
Jie Li ◽  
Zhixiong Li
Keyword(s):  
Decision Making ◽  
Data Base ◽  
Real Time ◽  
Manufacturing Industry ◽  
Job Shop ◽  
Data Driven ◽  
Dispatching Rules ◽  
Shop Floor ◽  
Production Data ◽  
Online Decision Making

In modern manufacturing industry, the methods supporting real-time decision-making are the urgent requirement to response the uncertainty and complexity in intelligent production process. In this paper, a novel closed-loop scheduling framework is proposed to achieve real-time decision making by calling the appropriate data-driven dispatching rules at each rescheduling point. This framework contains four parts: offline training, online decision-making, data base and rules base. In the offline training part, the potential and appropriate dispatching rules with managers’ expectations are explored successfully by an improved gene expression program (IGEP) from the historical production data, not just the available or predictable information of the shop floor. In the online decision-making part, the intelligent shop floor will implement the scheduling scheme which is scheduled by the appropriate dispatching rules from rules base and store the production data into the data base. This approach is evaluated in a scenario of the intelligent job shop with random jobs arrival. Numerical experiments demonstrate that the proposed method outperformed the existing well-known single and combination dispatching rules or the discovered dispatching rules via metaheuristic algorithm in term of makespan, total flow time and tardiness.

scholarly journals Sustainable, Smart, and Sensing Technologies for Cyber-Physical Manufacturing Systems: A Systematic Literature Review

2021 ◽  
Vol 13 (10) ◽  
pp. 5495
Author(s):  
Mihai Andronie ◽  
George Lăzăroiu ◽  
Roxana Ștefănescu ◽  
Cristian Uță ◽  
Irina Dijmărescu
Keyword(s):  
Decision Making ◽  
Internet Of Things ◽  
Literature Review ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Data Driven ◽  
Smart Manufacturing ◽  
Production Networks ◽  
Production Logistics ◽  
Time Production

With growing evidence of the operational performance of cyber-physical manufacturing systems, there is a pivotal need for comprehending sustainable, smart, and sensing technologies underpinning data-driven decision-making processes. In this research, previous findings were cumulated showing that cyber-physical production networks operate automatically and smoothly with artificial intelligence-based decision-making algorithms in a sustainable manner and contribute to the literature by indicating that sustainable Internet of Things-based manufacturing systems function in an automated, robust, and flexible manner. Throughout October 2020 and April 2021, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “Internet of Things-based real-time production logistics”, “sustainable smart manufacturing”, “cyber-physical production system”, “industrial big data”, “sustainable organizational performance”, “cyber-physical smart manufacturing system”, and “sustainable Internet of Things-based manufacturing system”. As research published between 2018 and 2021 was inspected, and only 426 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 174 mainly empirical sources. Further developments should entail how cyber-physical production networks and Internet of Things-based real-time production logistics, by use of cognitive decision-making algorithms, enable the advancement of data-driven sustainable smart manufacturing.

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