Fourth industrial revolution: a way forward to attain better performance in the textile industry

• Autorzy: Ślusarczyk Beata , Haseeb Muhammad , Hussain Hafezali Iqbal

Identyfikatory

DOI

10.2478/emj-2019-0011

• Języki publikacji: EN

Abstrakty

EN

The textile industry is one of the fastest growing industries which expressively contributes to the economic growth of Malaysia. However, in recent years, the situation has changed and demonstrates a downward trend. The imports are growing faster compared to the exports, consequently resulting in a low contribution to the gross domestic product (GDP). To address the issue, this study aims to investigate the role of Industry 4.0 on the performance of firms engaged in the production and services of the Malaysian textile industry. To achieve the objective, this study adopted a cross-sectional research design. A survey was carried out to collect data from employees of textile firms. Results of the study found that Industry 4.0 positively contributed to the effectiveness of the production and services of the textile industry. Production and services have a positive role in the performance of textile firms. The current study provides an interesting insight into the future direction of research for studies on organisational performance, which can be extended to different manufacturing-based industries. In addition, it provides the rationale for the adoption and implementation of smart technologies in these industries. It has been found that cyber-physical systems (CPS), interoperability, a smart city and a smart product have a positive effect on production and services. Additionally, it is not possible without the effective implementation of technology. Thus, the current study provides valuable insights into the improvement of the textile industry’s performance.

Słowa kluczowe

EN

Industry 4.0; firm performance; cyber physical system; interoperability; smart product; smart city

PL

Przemysł 4.0; wydajność firmy; system cyberfizyczny; interoperacyjność; inteligentny produkt; inteligentne miasto

• Wydawca: Oficyna Wydawnicza Politechniki Białostockiej
• Czasopismo: Engineering Management in Production and Services
• Rocznik: 2019
• Tom: Vol. 11, no. 2
• Strony: 52--69
• Opis fizyczny: Bibliogr. 122 poz., rys., tab.

Twórcy

autor

Ślusarczyk Beata

• Czestochowa University of Technology, Poland

autor

Haseeb Muhammad

• Taylor’s Business School (TBS), Malaysia

autor

Hussain Hafezali Iqbal

• Taylor’s Business School (TBS), Malaysia

Bibliografia

• Adner, R., & Kapoor, R. (2010). Value creation in innovation ecosystems: How the structure of technological interdependence affects firm performance in new technology generations. Strategic Management Journal, 31(3), 306-333.
• Alaeddin, O., Altounjy, R., Zainudin, Z., & Kamarudin, F. (2018). From physical to digital: investigating consumer behaviour of switching to mobile wallet. Polish Journal of Management Studies, 17(2), 18-30.
• Albers, A., Gladysz, B., Pinner, T., Butenko, V., & Sturmlinger, T. (2016). Procedure for defining the system of objectives in the initial phase of an industry 4.0 project focusing on intelligent quality control systems. Procedia CIRP, 52, 262-267.
• Ali, A., & Haseeb, M. (2019). Radio frequency identification (RFID) technology as a strategic tool towards higher performance of supply chain operations in textile and apparel industry of Malaysia. Uncertain Supply Chain Management, 7(2), 215-226.
• Almada-Lobo, F. (2016). The Industry 4.0 revolution and the future of manufacturing execution systems (MES). Journal of Innovation Management, 3(4), 16-21.
• Aral, S., & Weill, P. (2007). IT assets, organizational capabilities, and firm performance: How resource allocations and organizational differences explain performance variation. Organization Science, 18(5), 763-780.
• Bagheri, B., Yang, S., Kao, H.-A., & Lee, J. (2015). Cyberphysical systems architecture for self-aware machines in industry 4.0 environment. IFAC-Papers OnLine, 48(3), 1622-1627.
• Benitez-Amado, J., & Walczuch, R. M. (2012). Information technology, the organizational capability of proactive corporate environmental strategy and firm performance: a resource-based analysis. European Journal of Information Systems, 21(6), 664-679.
• Berre, A.-J., Elvesater, B., Figay, N., Guglielmina, C., Johnsen, S.G., Karlsen, D., Knothe, T., & Lippe, S. (2007). The ATHENA interoperability framework. In Goncalves, R.J., Muller, J.P., Mertins, K., & Zelm, M. (Eds.), Enterprise Interoperability II (pp. 569-580). London, United Kingdom: Springer.
• Biao, W., Zhao, J.-Y., Wan, Z.-G., Hong, L., & Jian, M. (2016). Lean Intelligent Production System and Value Stream Practice. DEStech Transactions on Economics, Business and Management (ICEM).
• Bondar, S., Hsu, J.C., Pfouga, A., & Stjepandić, J. (2017). Agile digital transformation of System-of-Systems architecture models using Zachman framework. Journal of Industrial Information Integration, 7, 33-43.
• Bornman, D.A.J. & Puth, G. (2017). Investigating employee perceptions of leadership communication: A South African study. Journal of Contemporary Management, 14(1), 1-23.
• Branger, J. (2015). Standardization perspectives of communication infrastructure of future homes: from automated home to sustainable, healthy and manufacturing home.
• Branger, J., & Pang, Z. (2015). From automated home to sustainable, healthy and manufacturing home: a new story enabled by the Internet-of-Things and Industry 4.0. Journal of Management Analytics, 2(4), 314-332.
• Brettel, M., Friederichsen, N., Keller, M., & Rosenberg, M. (2014). How virtualization, decentralization and network building change the manufacturing landscape: An Industry 4.0 Perspective. International Journal of Mechanical, Industrial Science and Engineering, 8(1), 37-44.
• Bryson, J.R., & Ronayne, M. (2014). Manufacturing carpets and technical textiles: routines, resources, capabilities, adaptation, innovation and the evolution of the British textile industry. Cambridge Journal of Regions, Economy and Society, 7(3), 471-488.
• Cao, B., Wang, Z., Shi, H., & Yin, Y. (2015). Research and practice on Aluminum Industry 4.0. Paper presented at the 2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP).
• Chen, D., Doumeingts, G., & Vernadat, F. (2008). Architectures for enterprise integration and interoperability: Past, present and future. Computers in Industry, 59(7), 647-659.
• Chen, Z., & Xing, M. (2015). Upgrading of textile manufacturing based on Industry 4.0. Paper presented at the 5th International Conference on Advanced Design and Manufacturing Engineering.
• Chu, W.-S., Kim, M.-S., Jang, K.-H., Song, J.-H., Rodrigue, H., Chun, D.-M., … & Cha, S. W. (2016). From design for manufacturing (DFM) to manufacturing for design (MFD) via hybrid manufacturing and smart factory: A review and perspective of paradigm shift. International Journal of Precision Engineering and Manufacturing-Green Technology, 3(2), 209-222.
• Colombo, J.A., Loncan, T.R., & Caldeira, J.F. (2018). Do foreign portfolio capital flows affect domestic investment? Evidence from Brazil. International Journal of Finance & Economics.
• Comrey, A., & Lee, H. (1992). A First Course in Factor Analysis (2nd edn.) Lawrence Earlbaum Associates. New Jersey, United States: Hillsdale.
• Creswell, J. W. (2009). Research designs: Qualitative, quantitative, and mixed methods approaches. Thousand Oaks, United States: Sage Publications.
• Dabas, N., Yadav, K.K., Ganguli, A.K., & Jha, M. (2019). New process for conversion of hazardous industrial effluent of ceramic industry into nanostructured sodium carbonate and their application in textile industry. Journal of Environmental Management, 240, 352-358.
• Davis, J., Edgar, T., Porter, J., Bernaden, J., & Sarli, M. (2012). Smart manufacturing, manufacturing intelligence and demand-dynamic performance. Computers & Chemical Engineering, 47, 145-156.
• Dilberoglu, U.M., Gharehpapagh, B., Yaman, U., & Dolen, M. (2017). The role of additive manufacturing in the era of industry 4.0. Procedia Manufacturing, 11, 545-554.
• Durana, P., Kral, P., Stehel, V., Lazaroiu, G., &Sroka, W. (2019) Quality Culture of Manufacturing Enterprises: A Possible Way to Adaptation to Industry 4.0. Social Sciences, 8, 124.
• Fornell, C., & Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 39-50.
• Gentner, S. (2016). Industry 4.0: Reality, Future or just Science Fiction? How to Convince Today’s Management to Invest in Tomorrow’s Future! Successful Strategies for Industry 4.0 and Manufacturing IT. CHIMIA International Journal for Chemistry, 70(9), 628-633.
• Georgakopoulos, D., Jayaraman, P.P., Fazia, M., Villari, M., & Ranjan, R. (2016). Internet of Things and Edge cloud computing roadmap for manufacturing. IEEE Cloud Computing, 3(4), 66-73.
• Geraci, A., Katki, F., McMonegal, L., Meyer, B., Lane, J., Wilson, P., … & Springsteel, F. (1991). IEEE standard computer dictionary: Compilation of IEEE standard computer glossaries. IEEE Press.
• Ghani, T., Armstrong, M., Auth, C., Bost, M., Charvat, P., Glass, G., … & Klaus, J. (2003). A 90nm high volume manufacturing logic technology featuring novel 45nm gate length strained silicon CMOS transistors. Paper presented at the IEEE International Electron Devices Meeting 2003.
• Gorecky, D., Schmitt, M., Loskyll, M., & Zuhlke, D. (2014). Human-machine-interaction in the industry 4.0 era. Paper presented at the 2014 12th IEEE International Conference on Industrial Informatics (INDIN).
• Gorkhali, A., & Xu, L.D. (2016). Enterprise application integration in industrial integration: a literature review. Journal of Industrial Integration and Management, 1(04), 1650014.
• Gray, B.J., & Hooley, G.J. (2002). Guest editorial: market orientation and service firm performance – a research agenda. European Journal of Marketing, 36(9/10), 980-989.
• Gurdur, D., El-Khoury, J., Seceleanu, T., & Lednicki, L. (2016). Making interoperability visible: Data visualization of cyber-physical systems development tool chains. Journal of Industrial Information Integration, 4, 26-34.
• Hair F.J., Sarstedt, M., Hopkins, L., & Kuppelwieser, V.G. (2014). Partial least squares structural equation modeling (PLS-SEM) An emerging tool in business research. European Business Review, 26(2), 106-121.
• Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E., & Tatham, R. (2010). Multivariate data analysis. Upper Saddle River, United States: Pearson Prentice Hall.
• Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E., & Tatham, R.L. (2006). Multivariate data analysis. Upper Saddle River, United States: Pearson Prentice Hall.
• Hair, J., Hollingsworth, C.L., Randolph, A.B., & Chong, A.Y.L. (2017). An updated and expanded assessment of PLS-SEM in information systems research. Industrial Management & Data Systems, 117(3), 442-458.
• Harrison, R., Vera, D., & Ahmad, B. (2016). Engineering methods and tools for cyber–physical automation systems. Proceedings of the IEEE, 104(5), 973-985.
• Haseeb, M., Hussain, H.I., Slusarcyzk, B. & Jermsittiparsert, K. (2019). Industry 4.0: A Solution towards Technology Challenges of Sustainable Business Performance. Social Sciences, 8(5), 154.
• Hettiarachchi, K., Talu, E., Longo, M. L., Dayton, P.A., & Lee, A.P. (2007). On-chip generation of microbubbles as a practical technology for manufacturing contrast agents for ultrasonic imaging. Lab on a Chip, 7(4), 463-468.
• Hong, Y.-P., Kim, Y., & Cin, B.C. (2015). Product-service system and firm performance: The mediating role of product and process technological innovation. Emerging Markets Finance and Trade, 51(5), 975-984.
• Hounshell, D. (1985). From the American system to mass production, 1800-1932: The development of manufacturing technology in the United States. Baltimore, United States: JHU Press.
• Hu, Q., & Huang, C.D. (2005). Aligning IT with firm business strategies using the balance scorecard system. Paper presented at the null.
• IARC - International Agency for Research on Cancer (1990). Some flame retardants and textile chemicals, and exposures in the textile manufacturing industry. IARC Monographs on the Evaluation of Carcinogenic Risks to Humans, 48.
• Ivanov, D., Dolgui, A., Sokolov, B., Werner, F., & Ivanova, M. (2016). A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory industry 4.0. International Journal of Production Research, 54(2), 386-402.
• Ivanov, D., Sokolov, B., & Ivanova, M. (2016). Schedule coordination in cyber-physical supply networks Industry 4.0. IFAC-PapersOnLine, 49(12), 839-844.
• Jazdi, N. (2014). Cyber physical systems in the context of Industry 4.0. Paper presented at the 2014 IEEE International Conference on Automation, Quality and Testing, Robotics.
• Jiang, P., Ding, K., & Leng, J. (2016). Towards a cyber-physical- social-connected and service-oriented manufacturing paradigm: Social Manufacturing. Manufacturing Letters, 7, 15-21.
• Kastalli, I.V., & van Looy, B. (2013). Servitization: Disentangling the impact of service business model innovation on manufacturing firm performance. Journal of Operations Management, 31(4), 169-180.
• Kobara, K. (2016). Cyber physical security for industrial control systems and IoT. IEICE Transactions on Information and Systems, 99(4), 787-795.
• Kokuryo, D., Kaihara, T., Suginouchi, S., & Kuik, S. (2016). A study on value co-creative design and manufacturing system for tailor-made rubber shoes production – Construction of value co-creative smart factory. Paper presented at the 2016 International Symposium on Flexible Automation (ISFA).
• Kolberg, D., & Zuhlke, D. (2015). Lean automation enabled by industry 4.0 technologies. IFAC-PapersOnLine, 48(3), 1870-1875.
• Kusters, D., Pras, N., & Gloy, Y.S. (2017). Textile Learning Factory 4.0–Preparing Germany’s Textile Industry for the Digital Future. Procedia Manufacturing, 9, 214-221.
• Lalic, B., Majstorovic, V., Marjanovic, U., Delić, M., & Tasic, N. (2017). The effect of industry 4.0 concepts and e-learning on manufacturing firm performance: evidence from transitional economy. Paper presented at the IFIP International Conference on Advances in Production Management Systems.
• Lasi, H., Fettke, P., Kemper, H.-G., Feld, T., & Hoffmann, M. (2014). Industry 4.0. Business & information systems engineering, 6(4), 239-242.
• Lee, J., Ardakani, H.D., Yang, S., & Bagheri, B. (2015). Industrial big data analytics and cyber-physical systems for future maintenance & service innovation. Procedia CIRP, 38, 3-7.
• Lee, J., Bagheri, B., & Kao, H.-A. (2015). A cyber-physical systems architecture for industry 4.0-based manufacturing systems. Manufacturing Letters, 3, 18-23.
• Lom, M., Pribyl, O., & Svitek, M. (2016). Industry 4.0 as a part of smart cities. Paper presented at the 2016 Smart Cities Symposium Prague (SCSP).
• Longo, F., Nicoletti, L., & Padovano, A. (2017). Smart operators in industry 4.0: A human-centered approach to enhance operators’ capabilities and competencies within the new smart factory context. Computers & Industrial Engineering, 113, 144-159.
• Lu, Y. (2017). Industry 4.0: A survey on technologies, applications and open research issues. Journal of Industrial Information Integration, 6, 1-10.
• Luftman, J.N., Lewis, P.R., & Oldach, S.H. (1993). Transforming the enterprise: The alignment of business and information technology strategies. IBM Systems Journal, 32(1), 198-221.
• Magnani, C., Comba, P., Ferraris, F., Ivaldi, C., Meneghin, M., & Terracini, B. (1993). A case-control study of carcinomas of the nose and paranasal sinuses in the woolen textile manufacturing industry. Archives of Environmental Health: An International Journal, 48(2), 94-97.
• Mao, J., Zhou, Q., Sarmiento, M., Chen, J., Wang, P., Jonsson, F., … & Zou, Z. (2016). A hybrid reader transceiver design for industrial internet of things. Journal of Industrial Information Integration, 2, 19-29.
• Meyer, N., & Meyer, D.F. (2016). The relationship between the creation of an enabling environment and economic development: A comparative analysis of management at local government sphere. Polish Journal of Management Studies, 14(2), 150-160.
• Mo, Y., & Sinopoli, B. (2016). On the performance degradation of cyber-physical systems under stealthy integrity attacks. IEEE Transactions on Automatic Control, 61(9), 2618-2624.
• Monostori, L., Kadar, B., Bauernhansl, T., Kondoh, S., Kumara, S., Reinhart, G., … & Ueda, K. (2016). Cyberphysical systems in manufacturing. Cirp Annals, 65(2), 621-641.
• Muller, J.M., Kiel, D., & Voigt, K.-I. (2018). What drives the implementation of industry 4.0? The role of opportunities and challenges in the context of sustainability. Sustainability, 10(1), 247.
• Muzekenyi, M.M., Zuwarimwe, J.Z., Kilonzo, B.M. & Nheta, D.S. (2019). An assessment of the role of real exchange rate on economic growth in South Africa. Journal of Contemporary Management, 16(1), 40-159.
• Nagy, J., Olah, J., Erdei, E., Mate, D., & Popp, J. (2018). The Role and Impact of Industry 4.0 and the Internet of Things on the Business Strategy of the Value Chain – The Case of Hungary. Sustainability, 10(10), 3491.
• Nii, J., Earl, M., & Ross, J. (1996). Eight imperatives for the new IT organisation. Sloan Management Review, 38(1), 43-55.
• Oesterreich, T.D., & Teuteberg, F. (2016). Understanding the implications of digitisation and automation in the context of Industry 4.0: A triangulation approach and elements of a research agenda for the construction industry. Computers in industry, 83, 121-139.
• Oses, N., Legarretaetxebarria, A., Quartulli, M., Garcia, I., & Serrano, M. (2016). Uncertainty reduction in measuring and verification of energy savings by statistical learning in manufacturing environments. International Journal on Interactive Design and Manufacturing (IJIDeM), 10(3), 291-299.
• Paelke, V. (2014). Augmented reality in the smart factory: Supporting workers in an industry 4.0. environment. Paper presented at the Proceedings of the 2014 IEEE emerging technology and factory automation (ETFA).
• Pang, Y.L., & Abdullah, A.Z. (2013). Current status of textile industry wastewater management and research progress in Malaysia: a review. Clean–Soil, Air, Water, 41(8), 751-764.
• Pang, Z., Zhengb, L., Tianb, J., Walterc-Kao, S., Dubrovab, E., & Chen, Q. (2015). Design of a terminal solution for integration of in-home health care devices and services towards the Internet-of-things. Enterprise Information Systems, 9, 86-116.
• Park, K.T., Kang, Y.T., Yang, S.G., Zhao, W.B., Kang, Y.S., Im, S.J., …. & Do Noh, S. (2019). Cyber Physical Energy System for Saving Energy of the Dyeing Process with Industrial Internet of Things and Manufacturing Big Data. International Journal of Precision Engineering and Manufacturing-Green Technology, 1-20.
• Perez, F., Irisarri, E., Orive, D., Marcos, M., & Estevez, E. (2015). A CPPS Architecture approach for Industry 4.0. Paper presented at the 2015 IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA).
• Pisching, M.A., Junqueira, F., Santos Filho, D.J., & Miyagi, P.E. (2015). Service composition in the cloud-based manufacturing focused on the industry 4.0. Paper presented at the Doctoral Conference on Computing, Electrical and Industrial Systems.
• Posada, J., Toro, C., Barandiaran, I., Oyarzun, D., Stricker, D., de Amicis, R., Pinto, E. B., Eisert, P., Dollner, J., & Vallarino, I. (2015). Visual computing as a key enabling technology for industrie 4.0 and industrial internet. IEEE Computer Graphics and Applications, 35(2), 26-40.
• Rai, H.S., Bhattacharyya, M.S., Singh, J., Bansal, T., Vats, P., & Banerjee, U. (2005). Removal of dyes from the effluent of textile and dyestuff manufacturing industry: a review of emerging techniques with reference to biological treatment. Critical Reviews in Environmental Science and Technology, 35(3), 219-238.
• Reich, B.H., & Benbasat, I. (2000). Factors that influence the social dimension of alignment between business and information technology objectives. MIS Quarterly, 81-113.
• Rivard, S., Raymond, L., & Verreault, D. (2006). Resourcebased view and competitive strategy: An integrated model of the contribution of information technology to firm performance. The Journal of Strategic Information Systems, 15(1), 29-50.
• Roblek, V., Meško, M., & Krapež, A. (2016). A complex view of industry 4.0. SAGE Open, 6(2), 1-11.
• Romero, D., & Vernadat, F. (2016). Enterprise information systems state of the art: Past, present and future trends. Computers in Industry, 79, 3-13.
• Rusmann, M., Lorenz, M., Gerbert, P., Waldner, M., Justus, J., Engel, P., & Harnisch, M. (2015). Industry 4.0: The future of productivity and growth in manufacturing industries. Boston Consulting Group, 9(1), 54-89.
• Saeidi, S.P., Sofian, S., Saeidi, P., Saeidi, S.P., & Saaeidi, S.A. (2015). How does corporate social responsibility contribute to firm financial performance? The mediating role of competitive advantage, reputation, and customer satisfaction. Journal of Business Research, 68(2), 341-350.
• Sandengen, O.C., Estensen, L.A., Rodseth, H., & Schjolberg, P. (2016). High Performance Manufacturing-An Innovative Contribution towards Industry 4.0. Paper presented at the 6th International Workshop of Advanced Manufacturing and Automation.
• Sanders, A., Elangeswaran, C., & Wulfsberg, J.P. (2016). Industry 4.0 implies lean manufacturing: Research activities in industry 4.0 function as enablers for lean manufacturing. Journal of Industrial Engineering and Management (JIEM), 9(3), 811-833.
• Scheuermann, C., Verclas, S., & Bruegge, B. (2015). Agile factory-an example of an industry 4.0 manufacturing process. Paper presented at the 2015 IEEE 3rd International Conference on Cyber-Physical Systems, Networks, and Applications.
• Schlechtendahl, J., Keinert, M., Kretschmer, F., Lechler, A., & Verl, A. (2015). Making existing production systems Industry 4.0-ready. Production Engineering, 9(1), 143-148.
• Schmidt, R., Mohring, M., Harting, R.-C., Reichstein, C., Neumaier, P., & Jozinović, P. (2015). Industry 4.0-potentials for creating smart products: empirical research results. Paper presented at the International Conference on Business Information Systems.
• Schuh, G., Gartzen, T., Rodenhauser, T., & Marks, A. (2015). Promoting work-based learning through industry 4.0. Procedia CIRP, 32, 82-87.
• Schumacher, A., Erol, S., & Sihn, W. (2016). A maturity model for assessing Industry 4.0 readiness and maturity of manufacturing enterprises. Procedia CIRP, 52, 161-166.
• Schuster, K., Plumanns, L., Gros, K., Vossen, R., Richert, A., & Jeschke, S. (2015). Preparing for Industry 4.0 –Testing Collaborative Virtual Learning Environments with Students and Professional Trainers. International Journal of Advanced Corporate Learning (IJAC), 8(4), 14-20.
• Shafiq, S.I., Sanin, C., Szczerbicki, E., & Toro, C. (2016). Virtual engineering factory: Creating experience base for industry 4.0. Cybernetics and Systems, 47(1-2), 32-47.
• Shafiq, S.I., Sanin, C., Toro, C., & Szczerbicki, E. (2015). Virtual engineering object (VEO): Toward experience- based design and manufacturing for industry 4.0. Cybernetics and Systems, 46(1-2), 35-50.
• Ślusarczyk, B. (2018). Industry 4.0 – Are we ready? Polish Journal of Management Studies, 17(1), 232-248.
• Smirnov, A., Sandkuhl, K., Shilov, N., & Kashevnik, A. (2013). “Product-Process-Machine” System Modeling: Approach and Industrial Case Studies. Paper presented at the IFIP Working Conference on The Practice of Enterprise Modeling.
• Sowell, P.K. (2006). The C4ISR Architecture Framework: History, Status, and Plans for Evolution. MITRE CORP MCLEAN VA.
• Stoel, M.D., & Muhanna, W.A. (2009). IT capabilities and firm performance: A contingency analysis of the role of industry and IT capability type. Information & Management, 46(3), 181-189.
• Sun, K.-A., & Kim, D.-Y. (2013). Does customer satisfaction increase firm performance? An application of American Customer Satisfaction Index (ACSI). International Journal of Hospitality Management, 35, 68-77.
• Tang, Z.W. (2015). The industrial robot is in conjunction with homework and system integration. Paper presented at the 5th International Conference on Information Engineering for Mechanics and Materials.
• Teo, T.S., & Ang, J.S. (1999). Critical success factors in the alignment of IS plans with business plans. International Journal of Information Management, 19(2), 173-185.
• Thames, L., & Schaefer, D. (2016). Software-defined cloud manufacturing for industry 4.0. Procedia CIRP, 52, 12-17.
• Theorin, A., Bengtsson, K., Provost, J., Lieder, M., Johnsson, C., Lundholm, T., & Lennartson, B. (2017). An event-driven manufacturing information system architecture for Industry 4.0. International Journal of Production Research, 55(5), 1297-1311.
• Thoben, K.-D., Busse, M., Denkena, B., & Gausemeier, J. (2014). System-integrated Intelligence – New Challenges for Product and Production Engineering in the Context of Industry 4.0. Procedia Technology, 15, 1-4.
• Tonelli, F., Demartini, M., Loleo, A., & Testa, C. (2016). A novel methodology for manufacturing firms value modeling and mapping to improve operational performance in the industry 4.0 era. Procedia CIRP, 57, 122-127.
• Tortorella, G.L., & Fettermann, D. (2018). Implementation of Industry 4.0 and lean production in Brazilian manufacturing companies. International Journal of Production Research, 56(8), 2975-2987.
• Tracey, M., Vonderembse, M.A., & Lim, J.-S. (1999). Manufacturing technology and strategy formulation: keys to enhancing competitiveness and improving performance. Journal of Operations Management, 17(4), 411-428.
• Wang, S., Wan, J., Zhang, D., Li, D., & Zhang, C. (2016). Towards smart factory for industry 4.0: a self-organized multi-agent system with big data based feedback and coordination. Computer Networks, 101, 158-168.
• Witkowski, J. Cheba, K., & Kiba-Janiak, M. (2017). The macro-and micro-environmental factors of decisions of production facility location by Japanese companies in Poland. Forum Scientiae Oeconomia, 5, 43-56.
• Yan, H., Xu, L.D., Bi, Z., Pang, Z., Zhang, J., & Chen, Y. (2015). An emerging technology – wearable wireless sensor networks with applications in human health condition monitoring. Journal of Management Analytics, 2(2), 121-137.
• Zawra, L.M., Mansour, H.A., Eldin, A.T., & Messiha, N.W. (2017). Utilizing the internet of things (IoT) technologies in the implementation of industry 4.0. Paper presented at the International Conference on Advanced Intelligent Systems and Informatics.
• Zhai, C., Zou, Z., Chen, Q., Xu, L., Zheng, L.-R., & Tenhunen, H. (2016). Delay-aware and reliability-aware contention-free MF–TDMA protocol for automated RFID monitoring in industrial IoT. Journal of Industrial Information Integration, 3, 8-19.
• Zhang, Y., Qian, C., Lv, J., & Liu, Y. (2017). Agent and cyber- physical system based self-organizing and selfadaptive intelligent shopfloor. IEEE Transactions on Industrial Informatics, 13(2), 737-747.
• Zhao, M., Droge, C., & Stank, T.P. (2001). The effects of logistics capabilities on firm performance: customer focused versus information‐focused capabilities. Journal of Business Logistics, 22(2), 91-107.
• Zheng, P., Sang, Z., Zhong, R.Y., Liu, Y., Liu, C., Mubarok, K., & Xu, X. (2018). Smart manufacturing systems for Industry 4.0: Conceptual framework, scenarios, and future perspectives. Frontiers of Mechanical Engineering, 13(2), 137-150.
• Zug, S., Wilske, S., Steup, C., & Luder, A. (2015). Online evaluation of manipulation tasks for mobile robots in Industry 4.0 scenarios. Paper presented at the 2015 IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA).
• Zuhlke, D., & Ollinger, L. (2011). Agile automation systems based on cyber-physical systems and service-oriented architectures. Advances in Automation and Robotics, 1, 567-574.