Many articles have been published on intelligent manufacturing, most of which focus on hardware, software, additive manufacturing, robotics, the Internet of Things, and Industry 4.0. This paper provides a different perspective by examining relevant challenges and providing examples of some less-talked-about yet essential topics, such as hybrid systems, redefining advanced manufacturing, basic building blocks of new manufacturing, ecosystem readiness, and technology scalability. The first major challenge is to (re-)define what the manufacturing of the future will be, if we wish to: ① raise public awareness of new manufacturing’s economic and societal impacts, and ② garner the unequivocal support of policymakers. The second major challenge is to recognize that manufacturing in the future will consist of systems of hybrid systems of human and robotic operators; additive and subtractive processes; metal and composite materials; and cyber and physical systems. Therefore, studying the interfaces between constituencies and standards becomes important and essential. The third challenge is to develop a common framework in which the technology, manufacturing business case, and ecosystem readiness can be evaluated concurrently in order to shorten the time it takes for products to reach customers. Integral to this is having accepted measures of “scalability” of non-information technologies. The last, but not least, challenge is to examine successful modalities of industry–academia–government collaborations through public–private partnerships. This article discusses these challenges in detail.
Information and communication technology is undergoing rapid development, and many disruptive technologies, such as cloud computing, Internet of Things, big data, and artificial intelligence, have emerged. These technologies are permeating the manufacturing industry and enable the fusion of physical and virtual worlds through cyber-physical systems (CPS), which mark the advent of the fourth stage of industrial production (i.e., Industry 4.0). The widespread application of CPS in manufacturing environments renders manufacturing systems increasingly smart. To advance research on the implementation of Industry 4.0, this study examines smart manufacturing systems for Industry 4.0. First, a conceptual framework of smart manufacturing systems for Industry 4.0 is presented. Second, demonstrative scenarios that pertain to smart design, smart machining, smart control, smart monitoring, and smart scheduling, are presented. Key technologies and their possible applications to Industry 4.0 smart manufacturing systems are reviewed based on these demonstrative scenarios. Finally, challenges and future perspectives are identified and discussed.
Reconfigurable manufacturing systems (RMSs), which possess the advantages of both dedicated serial lines and flexible manufacturing systems, were introduced in the mid-1990s to address the challenges initiated by globalization. The principal goal of an RMS is to enhance the responsiveness of manufacturing systems to unforeseen changes in product demand. RMSs are cost-effective because they boost productivity, and increase the lifetime of the manufacturing system. Because of the many streams in which a product may be produced on an RMS, maintaining product precision in an RMS is a challenge. But the experience with RMS in the last 20 years indicates that product quality can be definitely maintained by inserting in-line inspection stations. In this paper, we formulate the design and operational principles for RMSs, and provide a state-of-the-art review of the design and operations methodologies of RMSs according to these principles. Finally, we propose future research directions, and deliberate on how recent intelligent manufacturing technologies may advance the design and operations of RMSs.
It is costly and time consuming to use machining processes, such as grinding, polishing and lapping, to produce optical glass lenses with complex features. Precision glass molding (PGM) has thus been developed to realize an efficient manufacture of such optical components in a single step. However, PGM faces various technical challenges. For example, a PGM process must be carried out within the super-cooled region of optical glass above its glass transition temperature, in which the material has an unstable non-equilibrium structure. Within a narrow window of allowable temperature variation, the glass viscosity can change from 105 to 1012 Pa·s due to the kinetic fragility of the super-cooled liquid. This makes a PGM process sensitive to its molding temperature. In addition, because of the structural relaxation in this temperature window, the atomic structure that governs the material properties is strongly dependent on time and thermal history. Such complexity often leads to residual stresses and shape distortion in a lens molded, causing unexpected changes in density and refractive index. This review will discuss some of the central issues in PGM processes and provide a method based on a manufacturing chain consideration from mold material selection, property and deformation characterization of optical glass to process optimization. The realization of such optimization is a necessary step for the Industry 4.0 of PGM.
Manufacturing is the foundation of a nation’s economy. It is the primary industry to promote economic and social development. To accelerate and upgrade China’s manufacturing sector from “precision manufacturing” to “high-performance and high-quality manufacturing”, a new breakthrough should be found in terms of achieving a “leap-frog development”. Unlike conventional manufacturing, the fundamental theory of “Manufacturing 3.0” is beyond the scope of conventional theory; rather, it is based on new principles and theories at the atomic and/or close-to-atomic scale. Obtaining a dominant role at the international level is a strategic move for China’s progress.