Advanced Technologies in Life Cycle Engineering

Assessing relations between Circular Economy and Industry 4.0: a systematic literature review

“…x (Hughes 2017) x (Isaksson, Hallstedt, and Öhrwall Rönnbäck 2018) x (Jensen and Remmen 2017) x (Jin et al 2014) x (Kölsch et al 2017) x (Kowalkowski et al 2017) x (Kuo and Smith 2018) x (A. Q. Li and Found 2017) x (Liao et al 2017) x (Lopes de Sousa Jabbour et al 2018a) x (Lopes de Sousa Jabbour et al 2018b) x (Mařík et al 2016) x (Moreno and Charnley 2016) x (Neligan 2018) x (Okorie et al 2018) x (Pagoropoulos, Pigosso, and McAloone 2017) x (Planing 2017) x (Prendeville et al 2016) x (Rajala et al 2018) x (Ruggeri et al 2017) x (Sarkis and Zhu 2018) x (Shanshan Yang et al 2018) x (Sinclair et al 2018) x (Smart et al 2017) x (Srai et al 2016) x (Stark et al 2014) x (Stock and Seliger 2016) x (Thomas 2018) x (Tolio et al 2017) x (Townsend and Coroama 2018) x (Ünal, Urbinati, and Chiaroni 2018) x (X. Wang, Ong, and Nee 2018) x (Wilts and Berg 2017) x (B. Xu 2016)…”

“…Simulation was the prevalent technique, followed by AM, BDA, and the IoT. From one perspective, simulation (in the form of blockchain) was exploited for (i) auditing cooperative CE networks (Alexandris et al 2018), (ii) assessing the impact of business model changes (Simons 2017), for example, through agent-based or multi-method approaches , and (iii) assessing redistributed manufacturing or service-based design (Panarotto, Wall, and Larsson 2017) (French, Benakis, and Marin-Reyes 2017) x (Ge and Jackson 2014) x (Karastoyanov and Karastanev 2018) x (Kuik, Kaihara, and Fujii 2016) x (Lahrour and Brissaud 2018) x (Le, Paris, and Mandil 2017a) x (Le, Paris, and Mandil 2017b) x (Leino, Pekkarinen, and Soukka 2016) x (Liu et al 2016) x (Ruggeri et al 2017) x (Shanshan Yang et al 2018) x (Siddiqi et al 2017) x (Stark et al 2014) x (Tolio et al 2017) x (X. V. x (B. Xu 2016)…”

Smart design engineering: a literature review of the impact of the 4th industrial revolution on product design and development

“…According to Stark et al (2014b) one limitation of today's PLM solutions is the lack of intelligence to relieve engineers from some of the rather mundane data-management-centric activities, which become more complex due to the sheer amount of data now available and which also poses a challenge for maintaining systems-engineering traceability. They foresaw the evolution of intelligence in PLM solutions to support semi-automated data integration and decision support (artificial intelligence in PLM) up to the full automation of routine engineering activities, information linkage and multi-criteria decision support.…”

Continuous maintenance and the future – Foundations and technological challenges

“…In an effort to explore use of robots for autonomous maintenance, Fransworth and Tomiyama [42] have proposed a novel task classification for automation and collaborative robot application. solutions to interface conflicts between various multi-player systems, or to enable remote-servicing with mobile tele-cooperation devices via narrow-band connection are addressed [155]. Different kinds of IT systems are used for scheduling of MRO tasks, resource planning and communication.…”