Smart Innovation Engineering (SIE): Experience-Based Product Innovation System for Industry 4.0

2022

Automation

Digital Twins (DTs) are one of the disruptive technologies associated with the Industry 4.0 concept. A DT connects the physical manufacturing system with the digital cyberspace, via the synchronization of the simulation (i.e., physical configurations) and data models (i.e., product, process, and resource models) of the manufacturing system. This synchronization of both worlds—the physical and digital—allows one to address the issue of manufacturing customized products. This challenge of mass customization (1) puts forward the goal of achieving the highest level of customer satisfaction, and (2) creates the need for the optimization of the complete value creation process. Within an Industry 4.0 context, the latter is translated as the interlinking of production resources and systems, via a DT, as it is in the physical world where the actual value-creation process takes place. The success of an Industry 4.0 mass customization environment (or mass customization 4.0), depends on its degree/level of sustainability. For these reasons, the present paper presents a review of relevant concepts related to the role of DTs in the achievement of a mass customization 4.0 environment, plus some proposals of how to address the identified research challenges. A future research agenda is proposed at the end of the paper.

Section: Introductionmentioning

confidence: 99%

Towards the Development of a Digital Twin for a Sustainable Mass Customization 4.0 Environment: A Literature Review of Relevant Concepts

2022

Automation

“…e global dynamic competition impose manufacturing companies a series of business challenges such as operating with high levels of flexibility, efficiency, and adaptability in the face of product and process complexity [1], and to fast develop, design, and manufacture high quality, low cost, smart, mass customized products [2,3], at a reasonable cost and with reduced energy and resources consumption [4]. In this scenario, the business survival demands the ability to react to rapid product changes through reconfigurability [5], via the intensive use of automation, computer systems, and software [6].…”

Section: Introductionmentioning

confidence: 99%

“…0.388 0.060 0.015 0.000 0.104 0.000 0.149 0.045 0.239 M 1 0.388 0.060 0.015 0.000 0.104 0.000 0.000 0.000 0.000 M 2 0.776 0.119 0. 030 0.000 0.000 0.000 0.299 0.090 0.000 M 3 0.776 0.119 0.000 0.000 0.000 0.000 0.299 0.000 0.000 M 4 2.716 0.000 0.104 0.000 0.731 0.000 0.000 0.000 0.000 M 14 0.000 0.418 0.000 0.000 0.000 0.000 1.194 0.358 1.910 M 23 0.000 0.000 0.030 0.000 0.418 0.000 0.000 0.090 0.955 1.300 0.000 0.000 0.000 0.450 0.000 M 3 0.000 0.000 0.000 0.000 0.000 0.000 M 4 2.600 0.000 1.600 0.000 0.000 0.000 M 14 0.000 0.000 0.000 0.000 1.350 1.350 M 23 0.000 0.000 0.800 0.000 0.000 0.450 0.000 0.000 0.000 0.000 0.000 0.000 M 3 3.474 0.474 0.000 0.000 0.632 0.000 M 4 5.211 0.000 1.658 0.000 0.000 0.000 M 14 0.000 0.711 0.000 0.000 1.263 0.632 M 23 0.000 0.000 1.105 0.000 0.000 0.316 0.276 0.103 0.000 0.000 0.000 0.000 0.138 0.000 0.000 M 3 1.103 0.414 0.000 0.000 0.000 0.000 0.552 0.000 0.000 M 4 2.207 0.000 0.000 0.000 2.483 0.000 0.000 0.000 0.000 M 14 0.000 0.828 0.000 0.000 0.000 0.000 1.517 0.000 1.897 M 23 0.000 0.000 0.000 0.000 1.552 0.000 0.000 0.000 0.862 M 1 0.941 0.471 0.235 0.000 0.000 0.000 0.000 0.000 0.000 M 2 1.412 0.706 0.353 0.000 0.000 0.000 0.176 0.000 0.000 M 3 0.941 0.471 0.000 0.000 0.000 0.000 0.118 0.000 0.000 M 4 4.235 0.000 1.059 0.000 0.000 0.000 0.000 0.000 0.000 M 14 0.000 2.118 0.000 0.000 0.000 0.000 0.647 0.000 1.294 M 23 0.000 0.000 0.235 0.000 0.000 0.000 0.000 0.000 0.588 Mathematical Problems in Engineering Table 13, cursive letters).…”

unclassified

An Entropy-Based Formulation for Assessing the Complexity Level of a Mass Customization Industry 4.0 Environment

Mathematical Problems in Engineering

2020

It has been stated that Industry 4.0’s goal is, among others, the sustainable success in a market characterized by exigent and informed consumers demanding personalized products and services, where the level of manufacturing complexity increases with level of product customization. Even though different manufacturing complexity measures have been developed, there seems to be a lack of a comprehensive metric that address both the mass customization variety-induced complexity, and the complexity derived from the adoption of the Industry 4.0 paradigm. The main original contribution of this paper is the development of an entropy-based (entropic) formulation to address this last issue. Its validity and usefulness is put to the test via a discrete-event simulation study of a mass customization production system operating within an Industry 4.0 context. Our findings show that the entropic formulation acts as a fairly good trend indicator of the system’s performance parameter increase/decrease, but not as an estimator of the final values. A discussion of the managerial implications of the obtained results is offered at the end of the paper.

“…To fast develop, design, and manufacture high quality, low cost, smart, mass customized products [2,3], at a reasonable cost and with reduced energy and resources consumption [4].…”

mentioning

confidence: 99%

“…For this reason, the next section reviews the structural elements that influence it (manufacturing performance), as well as the relationship between sustainability, Industry 4.0 and value creation. Derived from this literature review, we proceed to define the research features, that is: (1) to identify the research gaps and opportunities; (2) to enunciate the research proposal (3) to establish the proposed research methodology; and (4) to highlight the research originality, usefulness and contributions.…”

mentioning

confidence: 99%

A Comprehensive Framework for the Analysis of Industry 4.0 Value Domains

Mora-Vargas

2019

Sustainability

Industry 4.0 aims to ensure the future competitiveness of the manufacturing industry by providing Companies with the ability to react to rapid product changes and disturbances, efficiently and reliably, through re-configurability. In this paper, we explore the value creation process within Industry 4.0, with special emphasis on its relationship with mass customization and the sustainability issue. Based on the identified research gaps and opportunities derived from a literature review of relevant concepts, we propose the development of the Customer-Product-Process-Resource (CPPR) 4.0, a comprehensive framework that puts the value proposition-creation-capture cycle proper of an Industry 4.0 environment, in the context of a manufacturing organization’s customer-product-process-resources views. The usefulness of the proposed framework is exemplified by using it to derive system dynamics model of the mass customization paradigm. A discussion of the managerial implications of the obtained results for both the sustainability and the case of Small-to-Medium Enterprises (SMEs) is offered at the end of the paper.