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Journal articles on the topic 'Manufacturing'

Author: Grafiati

Published: 4 June 2021

Last updated: 21 September 2024

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1

Begum, S. Gousia, A. Sireesha Bai, G. Kalpana, P. Mounika, and J. Aneesa Chandini. "REVIEW ON TABLET MANUFACTURING MACHINES AND TABLET MANUFACTURING DEFECTS." Indian Research Journal of Pharmacy and Science 5, no. 2 (2018): 1479–90. http://dx.doi.org/10.21276/irjps.2018.5.2.11.

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2

Roser, Christoph, Masaru Nakano, and Minoru Tanaka. "Holistic Manufacturing System Analysis(Advanced Manufacturing,Session: MP2-D)." Abstracts of the international conference on advanced mechatronics : toward evolutionary fusion of IT and mechatronics : ICAM 2004.4 (2004): 36. http://dx.doi.org/10.1299/jsmeicam.2004.4.36_2.

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3

Livesey, F. "Manufacturing clarity [manufacturing company]." Manufacturing Engineer 85, no. 5 (October 1, 2006): 22–23. http://dx.doi.org/10.1049/me:20060504.

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4

Roser, Christoph, Masaru Nakano, and Minoru Tanaka. "Time Shifting Bottlenecks in Manufacturing(Advanced Manufacturing,Session: MP2-D)." Abstracts of the international conference on advanced mechatronics : toward evolutionary fusion of IT and mechatronics : ICAM 2004.4 (2004): 37. http://dx.doi.org/10.1299/jsmeicam.2004.4.37_3.

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5

Xie, Guo Ru, and Wei An Xie. "Advanced Manufacturing Technology – Virtual Manufacturing." Applied Mechanics and Materials 543-547 (March 2014): 4638–41. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.4638.

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The main indicators of manufacturing companies competitiveness are time, quality, cost and related services, which make the manufacturing transform into new mode quickly. Manufacturing companies need flexibility and agility, so virtual manufacturing technology appeared. Virtual manufacturing is based on information technology, simulation technology and virtual reality technology. It can obtain many kinds of information by the aid of virtual environment. Before the design and manufacture of the product or system, virtual manufacturing can help people experience the performance and assembly relations of future product. Thus it can help people make decision and optimization scheme predictably.

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6

Northfield, R. "Manufacturing Futures 2021 [Manufacturing - Fashion]." Engineering & Technology 16, no. 9 (October 1, 2021): 24–26. http://dx.doi.org/10.1049/et.2021.0912.

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7

Zhou, Zude, Jerry Fuh, Shane Xie, and Zhongwei Jiang. "Digital Manufacturing and Cloud Manufacturing." Advances in Mechanical Engineering 5 (January 2013): 560691. http://dx.doi.org/10.1155/2013/560691.

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8

Chang, Shih‐Chia, Ru‐Jen Lin, Jung‐Hui Chen, and Li‐Hua Huang. "Manufacturing flexibility and manufacturing proactiveness." Industrial Management & Data Systems 105, no. 8 (October 2005): 1115–32. http://dx.doi.org/10.1108/02635570510624482.

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9

Harris, Gregory, Ashley Yarbrough, Daniel Abernathy, and Chris Peters. "Manufacturing Readiness for Digital Manufacturing." Manufacturing Letters 22 (October 2019): 16–18. http://dx.doi.org/10.1016/j.mfglet.2019.10.002.

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10

Banáš, Daniel, and Henrieta Hrablik Chovanová. "Agile Manufacturing vs. Lean Manufacturing." Research Papers Faculty of Materials Science and Technology Slovak University of Technology 31, no. 52 (June 1, 2023): 58–67. http://dx.doi.org/10.2478/rput-2023-0007.

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Abstract The aim of this paper is to describe characteristics of agile manufacturing and analyse the needs and benefits of agile manufacturing under the conditions of uncertainty and market turbulence. It also describes four main changes in the production environment which were implemented thanks to agile methods, and compares the lean and agile manufacturing, while describing their intersections and differences in achieving the set goals. The conclusion summarises the advantages and identified benefits suitable for organizations after implementation of agile manufacturing, as those are the important facts that can play a significant role in the survival and re-establishment of balance in the periods of uncertainty.

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MD AMIN, BOKHORI. "THE INFLUENCE OF HRM PRACTICES ON MANUFACTURING PERFORMANCE IN MALAYSIAN MANUFACTURING FIRMS." International Journal of Multidisciplinary Research and Studies 03, no. 09 (September 20, 2020): 01–15. http://dx.doi.org/10.33826/ijmras/v03i09.1.

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This study evaluated the relationship between compensation and performance, training and performance, and recruitment and performance on manufacturing' performance in manufacturing firms in Penang, Malaysia. A sample size of 222 respondents was taken from 28 electrical manufacturing firms with a 6322 population and 361 samples to examine the relationship. A questionnaire was designed for data collection to measure compensation and performance, training and performance, and recruitment and performance on employees' performance in manufacturing firms. A stratified sampling method was used, and the data was analyzed using SmartPls 3.7.8. The study showed that compensation and performance, training and performance, and recruitment and performance have a significant relationship with manufacturing' performance in manufacturing firms. However, the limitation of this study only covers electrical manufacturing firms. Suggested for future study focus on electronic, plastic, and fabricated manufacturing firms to be more effective in improving manufacturing firms' performance.

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12

Willis, Richard. "Manufacturing." Asia Pacific Viewpoint 42, no. 1 (April 2001): 67–74. http://dx.doi.org/10.1111/1467-8373.00133.

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13

Rose, Dennis. "Manufacturing." Pacific Viewpoint 32, no. 2 (October 1991): 171–80. http://dx.doi.org/10.1111/apv.322008.

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14

Košťál, Peter, and Daynier Rolando Delgado Sobrino. "Flexible Manufacturing System for Drawingless Manufacturing." Key Engineering Materials 581 (October 2013): 527–32. http://dx.doi.org/10.4028/www.scientific.net/kem.581.527.

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Flexible Manufacturing Systems provide a fast reaction possibility to the changes in production conditions. As production conditions change, other changes in the final product like changes of the product variants, or other unpredictable events may be also expected. For achieving a quick responsibility of production, it is necessary to leave the traditional form of production process planning. Nowadays most of the products are designed by using the CAx software. The product design 3D model contains not only the geometrical data of product, but may contain a part of the process plan and technological data as well.

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15

Frăţilă, Domniţa, and Horaţiu Rotaru. "Additive manufacturing – a sustainable manufacturing route." MATEC Web of Conferences 94 (2017): 03004. http://dx.doi.org/10.1051/matecconf/20179403004.

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16

Adekanye, S. A., R. M. Mahamood, E. T. Akinlabi, and M. G. Owolabi. "Additive manufacturing: the future of manufacturing." Materiali in tehnologije 51, no. 5 (October 16, 2017): 709–15. http://dx.doi.org/10.17222/mit.2016.261.

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17

Xing, Bo, Jesse Eganza, Glen Bright, and J. Potgieter. "RECONFIGURABLE MANUFACTURING SYSTEM FOR AGILE MANUFACTURING." IFAC Proceedings Volumes 39, no. 3 (2006): 509–16. http://dx.doi.org/10.3182/20060517-3-fr-2903.00265.

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18

Fox, S. "Manufacturing goes online [advanced manufacturing technology]." Engineering & Technology 4, no. 15 (September 12, 2009): 62–63. http://dx.doi.org/10.1049/et.2009.1512.

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19

Thomé, Antônio Márcio Tavares, and Rui Sousa. "Design-manufacturing integration and manufacturing complexity." International Journal of Operations & Production Management 36, no. 10 (October 3, 2016): 1090–114. http://dx.doi.org/10.1108/ijopm-11-2014-0550.

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Purpose The purpose of this paper is to propose that the effectiveness of organizational design-manufacturing integration (ODMI) practices is contingent upon the degree of complexity of the manufacturing environment. The paper submits that the level of use of ODMI ought to match the level of complexity of the manufacturing environment. The paper puts forward the hypothesis that when a misfit occurs between ODMI and complexity (high use of ODMI practices in low complexity environments or low use of ODMI practices in high complexity environments) manufacturing operational performance declines. Design/methodology/approach The paper tests the hypothesis based on a survey database of 725 manufacturers from 21 countries. The measurement model was assessed with confirmatory factor analysis and the hypothesis was tested with linear regression. Findings A misfit between the level of ODMI use (job rotation and co-location) and manufacturing complexity (product and process complexity) has a negative effect on manufacturing operational performance dimensions of quality, delivery and flexibility. Post hoc analyses also suggest that firms that operate in different environments in what concerns the rate of change in process technologies suffer differentiated negative impacts of ODMI-complexity misfit. Research limitations/implications Future studies could extend this research to other dimensions of design-manufacturing integration, such as technological practices. Practical implications Manufacturers with high levels of complexity should invest strongly in ODMI practices. However, manufacturers with low levels of complexity should invest in these practices with caution since the expected payoffs may not outweigh the effort. Originality/value The study assesses fit as a simultaneous set of contingency factors, applying profile-deviation analysis to ODMI and operational performance relationships. By focusing on plant-level manufacturing complexity, this study complements existing studies of product development complexity which tend to focus on project-level complexity.

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20

Zhang, Lin, Yongliang Luo, Fei Tao, Bo Hu Li, Lei Ren, Xuesong Zhang, Hua Guo, Ying Cheng, Anrui Hu, and Yongkui Liu. "Cloud manufacturing: a new manufacturing paradigm." Enterprise Information Systems 8, no. 2 (May 21, 2012): 167–87. http://dx.doi.org/10.1080/17517575.2012.683812.

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21

Yuan, Minghai, Kun Deng, and W. A. Chaovalitwongse. "Manufacturing Resource Modeling for Cloud Manufacturing." International Journal of Intelligent Systems 32, no. 4 (November 1, 2016): 414–36. http://dx.doi.org/10.1002/int.21867.

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22

Herwanto, Ion Sheren Dheril, and Ali Akbar. "Conveyor Roll Manufacturing Conveyor Roll Manufacturing." Procedia of Engineering and Life Science 7 (March 14, 2024): 352–54. http://dx.doi.org/10.21070/pels.v7i0.1483.

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Field work practice is a form of educational and vocational implementation that is participated in by students. Practical work aims to prepare students to become productive people and can work directly in their respective fields. Students can also experience the production atmosphere and can help deal with several problems experienced by professional engineering in factories. Conveyor systems can be said to be part of the equipment mechanics that transport materials from one place to another. This system is useful when goods need to be transported and moved from one place to another. Its existence makes the process easier, faster and more comfortable. In various industries, conveyors are very important. This system is designed to withstand heavy workloads and extreme weather conditions. The ability to adjust certain angles to help move materials. Design is divided into two, namely planning and conceptualizing. Planning this research focused on designing the conveyor for the can and plastic bottle waste sorting machine, then the consumer needs for the conveyor for the can and plastic bottle waste sorting machine were arranged as follows: a) The conveyor is easy to operate. b) Does not endanger the operator. c) Easy maintenance. d) Energy efficient conveyor from carrying out practical field work at CV. According to Agung Widodo's source, it can be concluded as follows: Industrial Automation or Industrial Automation is basically technology related to the application of mechanical, electronic and computer-based information systems to operate and control production.

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23

Xiao, Wenlei, Tianze Qiu, Qiang Liu, Gang Zhao, Hongwen Xing, and Rupeng Li. "Manufacturing crisis and twin-oriented manufacturing." Journal of Manufacturing Systems 73 (April 2024): 205–22. http://dx.doi.org/10.1016/j.jmsy.2024.02.002.

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24

SOZON, Tsopanos. "Laser Additive Manufacturing (LAM)." JOURNAL OF THE JAPAN WELDING SOCIETY 83, no. 4 (2014): 266–69. http://dx.doi.org/10.2207/jjws.83.266.

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25

Tilavaldiev, Bakhtiyar. "METHODS OF MANUFACTURING GEARS." International Journal of Advance Scientific Research 02, no. 11 (November 1, 2022): 127–30. http://dx.doi.org/10.37547/ijasr-02-11-19.

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This article discusses the manufacture of gears with two methods (copy method and run-in method). The largest number of gear wheels are made of carbon and alloy steels, and less often of cast iron, bronze and plastic. In the manufacture of gears, two fundamentally different methods are used. copy method and run method. Gears, especially high-precision gears, must have dimensional stability, therefore, in their manufacture, high requirements are placed on material homogeneity and balance of internal stresses.

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26

Shahbazi, Zeinab, and Yung-Cheol Byun. "Improving Transactional Data System Based on an Edge Computing–Blockchain–Machine Learning Integrated Framework." Processes 9, no. 1 (January 4, 2021): 92. http://dx.doi.org/10.3390/pr9010092.

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The modern industry, production, and manufacturing core is developing based on smart manufacturing (SM) systems and digitalization. Smart manufacturing’s practical and meaningful design follows data, information, and operational technology through the blockchain, edge computing, and machine learning to develop and facilitate the smart manufacturing system. This process’s proposed smart manufacturing system considers the integration of blockchain, edge computing, and machine learning approaches. Edge computing makes the computational workload balanced and similarly provides a timely response for the devices. Blockchain technology utilizes the data transmission and the manufacturing system’s transactions, and the machine learning approach provides advanced data analysis for a huge manufacturing dataset. Regarding smart manufacturing systems’ computational environments, the model solves the problems using a swarm intelligence-based approach. The experimental results present the edge computing mechanism and similarly improve the processing time of a large number of tasks in the manufacturing system.

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27

TAKECHI, Hideo, and Tadashi ISHIKETA. "ARTIFICIAL INTELLIGENCE FOR QUERY INFERENCE IN MANUFACTURING MANAGEMENT DATABASE(Manufacturing systems and Scheduling)." Proceedings of International Conference on Leading Edge Manufacturing in 21st century : LEM21 2005.2 (2005): 409–14. http://dx.doi.org/10.1299/jsmelem.2005.2.409.

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28

Clark, Kim B. "COMPETING THROUGH MANUFACTURING AND THE NEW MANUFACTURING PARADIGM: IS MANUFACTURING STRATEGY PASSE?" Production and Operations Management 5, no. 1 (January 5, 2009): 42–58. http://dx.doi.org/10.1111/j.1937-5956.1996.tb00384.x.

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29

Ocampo, Lanndon, and Eppie Clark. "Integrating Sustainability and Manufacturing Strategy into a Unifying Framework." International Journal of Social Ecology and Sustainable Development 8, no. 1 (January 2017): 1–16. http://dx.doi.org/10.4018/ijsesd.2017010101.

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The direction of current literature in addressing sustainability issues in the manufacturing sector highlights some models and approaches that are usually based on the concept of the triple-bottom line. However, as a functional unit in a manufacturing organization, the role of the manufacturing function in creating competitiveness has been outdone by the current demands of sustainability such that integrating sustainability and competitiveness remains a significant gap. This paper proposes a unifying framework in formulating a manufacturing strategy which espouses sustainability with due consideration of the manufacturing's internal and external competitive functions. The proposed framework integrates the features based on the classical theories of manufacturing strategy and the other features that must be considered to transform a firm's manufacturing strategy into a sustainable manufacturing strategy. This framework serves as a guide for decision-makers in identifying policies in various manufacturing decision areas that would comprise a sustainable manufacturing strategy. Results of recent empirical studies that are based on the models generated from the framework are reported in this paper.

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30

Bazhanov, Viktor A. "State regulation of manufacturing and manufacturing markets." World of Economics and Management 20, no. 2 (2020): 5–23. http://dx.doi.org/10.25205/2542-0429-2020-20-2-5-23.

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The article gives a brief overview of key state legal, regulatory and forecast documents related to government regulation of production and the Russian manufacturing market developed and adopted in the second decade of this century. On the example of the implementation of government measures aimed at improving the structure of industrial production and solving the problems of staffing the functioning of manufacturing industries, unresolved problems in these areas of state regulation that persist at the end of the second decade are shown. Examples of foreign experience and some recommendations in the field of state regulation of the country's industrial development are given. It is shown that for radical investment growth, it is necessary to first of all solve structural problems in the economy, implement measures aimed at improving the business climate, developing competition and reducing the share of the public sector and stimulating consumer demand to intensify the investment activities of private business in the field of manufacturing. In order to accurately and reasonably assess the impact of government measures on the development of manufacturing in the country, it is necessary to develop a methodology for assessing the regulatory impact (ODS) in the direction of methods for assessing the impact of government decisions on the activation of innovation and the use of progressive technologies "Industry 4.0."

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31

MARUO, Shoji. "Next-generation Manufacturing based on Additive Manufacturing." Proceedings of Mechanical Engineering Congress, Japan 2021 (2021): K221–01. http://dx.doi.org/10.1299/jsmemecj.2021.k221-01.

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32

Liu, Hong Jun, Qing Ming Fan, and Tong Xiao Yan. "Manufacturing Information Model for Design for Manufacturing." Applied Mechanics and Materials 249-250 (December 2012): 415–19. http://dx.doi.org/10.4028/www.scientific.net/amm.249-250.415.

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In the light of growing global competition, organizations around the world today are constantly under pressure to produce high-quality products at an economical price. The integration of design and manufacturing (DFM) activities into one common engineering effort has been recognized as a key strategy for survival and growth. In this paper, the importance of DFM and parts information model was introduced in today's manufacturing enterprise. It describes the classification of parts information model; namely: product models, process models and cost models, the main content and research status that the model contained. The author has proposed a semantic network description method of the manufacture parts information of and details its main content, which is the core of this paper.

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33

Nawanir, Gusman, Kong Teong Lim, and Siti Norezam Othman. "Lean manufacturing practices in Indonesian manufacturing firms." International Journal of Lean Six Sigma 7, no. 2 (June 6, 2016): 149–70. http://dx.doi.org/10.1108/ijlss-06-2014-0013.

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Purpose Contradictory findings regarding the implication of Lean manufacturing (LM) implementation to business performance (BP) have been observed in prior studies. Hence, more studies are required to be capable of finding the status of LM implementation and its impacts on BP. Accordingly, this study examines and scrutinizes the effects of LM practices on the enhancement of BP from a developing country standpoint. Design/methodology/approach This empirical study uses a survey-based quantitative data collection approach through a cross-sectional research design. A total of 139 large manufacturing companies in Indonesia participated, selected through stratified random sampling technique. Three hypotheses regarding the effect of LM on BP were examined. Findings The results empirically reveal that comprehensive implementation of LM practices is necessary. Also, this study unravels that high BP (in terms of profitability, sales and customer satisfaction) is dependent upon the comprehensive implementation of LM practices. In other words, LM practices are not recommended to be implemented as a subset. Research limitations/implications Although this study is free from the common method bias as an implication of self-reporting by single respondent from one company, future researchers should consider of collecting data from multiple individuals in one company. Additionally, due to the study conducted in limited industries and large manufacturing firms, the results may not be applicable in other industries as well as in small and medium enterprises. Practical implications This study has further confirmed and established the LM–BP relationship. In line with the complementarity theory, it provides an insight that all the LM practices should be implemented simultaneously in a holistic manner because they are mutually supportive. In such a situation, piecemeal adoption is highly not recommended. Originality/value This study emphasizes on how LM contributes to the superior BP. Meanwhile, little attention has been paid to investigate the LM and its implication on BP from a developing country standpoint. Thus, this study is initiated to fill the gap.

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34

Mahapatra, Santosh, Raktim Pal, and Ram Narasimhan. "Hybrid (re)manufacturing: manufacturing and operational implications." International Journal of Production Research 50, no. 14 (July 15, 2012): 3786–808. http://dx.doi.org/10.1080/00207543.2011.588615.

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35

MIZUTANI, Masayoshi. "Paradigm Shift from Manufacturing to “Function Manufacturing”." Journal of the Japan Society for Precision Engineering 88, no. 10 (October 5, 2022): 745–48. http://dx.doi.org/10.2493/jjspe.88.745.

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36

Lei, Qi, Qi Feng Wang, and Yu Chuan Song. "Manufacturing Service Integration Architecture for Networked Manufacturing." Materials Science Forum 626-627 (August 2009): 801–6. http://dx.doi.org/10.4028/www.scientific.net/msf.626-627.801.

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Intense competition drives the need for dynamic integration of dispersed and heterogeneous manufacturing services. This paper proposes a kind of semantic-based service integration architecture for networked manufacturing. A unique property of this architecture is that it provides the unified interface encapsulation approach and semantic analyzing method to realize dynamic and loose coupling integration. Some key technologies are introduced to demonstrate how the proposed integration architecture can be used to establish a collaborative environment, wherein manufacturing services are semantic modeled, semantic analyzed, and dynamically integrated on-demand.

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37

SUBRAMANIAM, ARUNACHALAM, XAVIER ROSELIN SOPHIA FRANCIS, and EDOHIS ALOYSIUS A. "CLOUD MANUFACTURING - A BOON FOR MANUFACTURING SMEs." i-manager’s Journal on Cloud Computing 4, no. 1 (2017): 23. http://dx.doi.org/10.26634/jcc.4.1.13755.

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38

Cheng, Yang, Sami Farooq, and John Johansen. "Manufacturing network evolution: a manufacturing plant perspective." International Journal of Operations & Production Management 31, no. 12 (November 15, 2011): 1311–31. http://dx.doi.org/10.1108/01443571111187466.

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39

Nasution, Abdillah Arif, Ikhsan Siregar, Anizar, Tigor Hamonangan Nasution, Khalida Syahputri, and Indah Rizkya Tarigan. "Lean Manufacturing Applications in the Manufacturing Industry." MATEC Web of Conferences 220 (2018): 02005. http://dx.doi.org/10.1051/matecconf/201822002005.

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This research was conducted in manufacturing industry, so this research is based on case study application. This research serves to reduce waste in the industry when making a product. This study categorizes value-added work and which work has no added value. And it is measurable and has value, so it can be evaluated in the future. Later this will be poured or depicted on a map called Value stream mapping. This is a tool from Lean Manufacturing. Lean manufacturing is useful for analysing and reducing non value-added activities, value stream mapping analysis tools, 5L1H process mapping activities, and 5 why tools. From the results of this study obtained the efficiency of the process cycle and total estimation of the improvement of the lead time. This calculation can be an evaluation material for the company.

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40

Baker, R. P., and P. G. Maropoulos. "Manufacturing capability measurement for cellular manufacturing systems." International Journal of Production Research 36, no. 9 (September 1998): 2511–27. http://dx.doi.org/10.1080/002075498192661.

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41

Voss, Christopher A. "Implementing Manufacturing Technology: A Manufacturing Strategy Approach." International Journal of Operations & Production Management 6, no. 4 (April 1986): 17–26. http://dx.doi.org/10.1108/eb054769.

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42

Ghosh, Manimay. "Lean manufacturing performance in Indian manufacturing plants." Journal of Manufacturing Technology Management 24, no. 1 (December 14, 2012): 113–22. http://dx.doi.org/10.1108/17410381311287517.

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43

Dangayach, G. S., and S. G. Deshmukh. "Manufacturing strategy: Experiences from Indian manufacturing companies." Production Planning & Control 12, no. 8 (January 2001): 775–86. http://dx.doi.org/10.1080/09537280110046608.

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44

Qiao, Guixiu, Roberto F. Lu, and Charles McLean. "Flexible manufacturing systems for mass customisation manufacturing." International Journal of Mass Customisation 1, no. 2/3 (2006): 374. http://dx.doi.org/10.1504/ijmassc.2006.008631.

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45

Prakash, K. Satish, T. Nancharaih, and V. V. Subba Rao. "Additive Manufacturing Techniques in Manufacturing -An Overview." Materials Today: Proceedings 5, no. 2 (2018): 3873–82. http://dx.doi.org/10.1016/j.matpr.2017.11.642.

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46

Hon, KKB, and F. J. Lopez-Jaquez. "Configuration of Manufacturing Cells for Dynamic Manufacturing." CIRP Annals 51, no. 1 (2002): 391–94. http://dx.doi.org/10.1016/s0007-8506(07)61544-3.

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47

Wilkinson, Joe. "Taking the manufacturing order out of manufacturing." Logistics Information Management 8, no. 2 (April 1995): 45–48. http://dx.doi.org/10.1108/09576059510815682.

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48

P. Cooper, Khershed, and Ralph F. Wachter. "Cyber-enabled manufacturing systems for additive manufacturing." Rapid Prototyping Journal 20, no. 5 (August 12, 2014): 355–59. http://dx.doi.org/10.1108/rpj-01-2013-0001.

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Purpose – The purpose of this paper is to study cyber-enabled manufacturing systems (CeMS) for additive manufacturing (AM). The technology of AM or solid free-form fabrication has received considerable attention in recent years. Several public and private interests are exploring AM to find solutions to manufacturing problems and to create new opportunities. For AM to be commercially accepted, it must make products reliably and predictably. AM processes must achieve consistency and be reproducible. Design/methodology/approach – An approach we have taken is to foster a basic research program in CeMS for AM. The long-range goal of the program is to achieve the level of control over AM processes for industrial acceptance and wide-use of the technology. This program will develop measurement, sensing, manipulation and process control models and algorithms for AM by harnessing principles underpinning cyber-physical systems (CPS) and fundamentals of physical processes. Findings – This paper describes the challenges facing AM and the goals of the CeMS program to meet them. It also presents preliminary results of studies in thermal modeling and process models. Originality/value – The development of CeMS concepts for AM should address issues such as part quality and process dependability, which are key for successful application of this disruptive rapid manufacturing technology.

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49

Mubarok, Khamdi, Xun Xu, Xinfeng Ye, Ray Y. Zhong, and Yuqian Lu. "Manufacturing service reliability assessment in cloud manufacturing." Procedia CIRP 72 (2018): 940–46. http://dx.doi.org/10.1016/j.procir.2018.03.074.

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Esmaeel, Raghed Ibrahim, Norhayati Zakuan, Noriza Mohd Jamal, and Hamed Taherdoost. "Fit manufacturing; integrated model of manufacturing strategies." Procedia Manufacturing 22 (2018): 975–81. http://dx.doi.org/10.1016/j.promfg.2018.03.139.

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