Management of automation and advanced manufacturing technology (AAMT) in the context of global manufacturing

Automation and advanced manufacturing technology solutions (AAMT) that present tangible and intangible benefits remain key drivers for manufacturers from both the developed and developing countries. However, the reality is that some manufacturing companies exploit the benefits of AAMT more effectively than others and develop their competitive advantage.

Historically, the International Journal of Production Research (IJPR) has been instrumental in disseminating research on the challenges and benefits associated with new manufacturing technologies and this research has predominantly been documented from either an Operations Research (OR) or an Operations Management (OM) perspective. In the 1980s, IJPR publications drew attention to a range of OR issues including justification techniques (e.g. Mkrkdtth and Surksh 1986), layout design (e.g. Aneke and Carrie 1986), flow optimisation (e.g. Kimemia and Gershwin 1985) and distributed scheduling using local area networks (Shaw 1987). At the same time publications from an OM perspective included implementation issues (e.g. Carrier et al. 1984), diffusion studies (e.g. Hyer and Wemmerlov 1989), and visions of future manufacturing paradigms (e.g. Bullinger, Warnecke, and Lentes 1986; Plossl 1988; Primrose and Leonard 1988).

In the 1990s, OM IJPR publications on manufacturing technologies increased the focus on technology sourcing (e.g. Baines 1999), strategic appraisal techniques (e.g. Naik and Chakravarty 1992; Gupta 1993) and implementation issues (e.g. Ramamurthy 1994; Silveira 1999). Meanwhile, the exploration of new manufacturing paradigms continued with, for example, disassembly systems (Ng, Ip, and Lee 1999), the virtual enterprise (e.g. Zhou 1999) and rapid prototyping and extendible systems (Weston 1998). Similarly, OR studies continued into new areas including ‘design for’ new systems (e.g. Ngoi and Fang 1994), optimal use (e.g. Dong and Vijayan 1997) and improvement of new systems using sophisticated modelling techniques (see e.g. Suresh and Kaparthi 1994; Venugopal and Narendran 1994; Talluri, Huq, and Pinney 1997; Cheng-Leong, Li Pheng, and Keng Leng 1999; Zhang et al. 1999).

At the dawn of the new millennium, IJPR publications on manufacturing technology still concerned conceptual and survey work on new paradigms including web-based (Yang and Xue 2003) or factory less (Bateman and Cheng 2006) manufacturing systems, reconfigurable manufacturing systems (Abdi and Labib 2003), or the application of augmented reality technologies in manufacturing (Ong, Yuan, and Nee 2008). Publications also concerned more practical challenges associated with the use or limitations of modern technologies including the need for flexible fixture design (Bi and Zhang 2001), the need for ontologies to support interoperability (Lin, Harding, and Shahbaz 2004) and application-oriented research concerning for example the use of RFID (Liu and Chen 2009) and of collaborative autonomous agents (Ratchev, Shiau, and Valtchanov 2000). Parallel to such publications focusing on the potential or use of specific technologies and dealing with objective challenges, a stream of OM research focused on the broader topics of selection, implementation and performance of ‘advanced manufacturing technology’ (AMT). Traces of such research were also evident in IJPR and included publications on managerial challenges (Sohal et al. 2006) such as human factors (e.g. Machuca, Díaz, and Gil 2004) and contingencies related to manufacturing strategy (e.g. Das and Jayaram 2003) or the environment affecting performance-technology links. However, in the past few years, studies of the AMT-performance link and related selection and implementation challenges have dropped in number. Meanwhile, the OR stream continued to develop advanced optimisation and modelling schemes for emerging technologies or new types of manufacturing systems including for example advanced modelling of processing operations (e.g. Chan, Kwong, and Tsim 2010; Sanz-Lobera et al. 2015), applications of RFID in wireless manufacturing (Zhang et al. 2011), partner selection in virtual manufacturing (Tao et al. 2012), models for investments in premature technologies (Peters 2015) and the incorporation of sustainability considerations in various decisions (e.g. Lee and Prabhu 2015).

In contrast to the studies in the 1990’s, the word AMT in the recent past has begun to encompass nascent process technologies such as additive manufacturing, nano-engineering and fabrication (e.g. Gardan 2016; Wang et al. 2016; Achillas, Tzetzis, and Raimondo 2017). Nevertheless, these technology developments and their industrial application have not been truly reflected in the existing studies and the research in this domain is still in an embryonic stage with very few studies of manufacturing technology implementation or of transition processes towards new manufacturing paradigms. Therefore, we suggest that in order to close the time gap between research and diffusion of new technologies, paradigms, and techniques, there is a need for more cross-disciplinary exchange as well as collaboration with practitioners to better understand the practical obstacles and limitations that continue to keep diffusion rates of futuristic scenarios low. We consider AAMT as an umbrella term for the different dimensions of manufacturing technology research and application to remind ourselves that technology studies need to cover all stages from conceptualisation to adoption to problem solving and exploitation. Therefore, this special issue has been aimed to collect an amalgam of modern AAMT studies to highlight the development of the field.

The study by Borges and Tan uses action research to test and refine a procedure aimed at identifying, evaluating and prioritising human factors that may facilitate or obstruct full realisation of the potential benefits of new technologies in the technology selection stage through the involvement of various stakeholders. The study by Harrington, Phillips and Srai uses a series of workshops and literature to identify and assess barriers that hinder the implementation of new technologies, thereby supporting the transition away from batch processing to more continuous production in the pharmaceutical industry. They find that while technological barriers still exist, several barriers are related to the need for new value networks. Long, Pan, Zhang and Hao elaborate the potential impacts of 3D printing by considering the changing face of Chinese manufacturing in the light of the increasing challenges associated with rising labour and energy costs in the country and with the high energy consumption and low tech nature of the sector. The need to move into markets for customised products and distributed manufacturing, support innovation and reduce life cycle material, water and energy input are identified as some of the key benefits of additive manufacturing adoption for the Chinese manufacturing sector. Li, Jia, Cheng and Hu use system dynamics modelling to compare conventional centralised spare parts supply networks with multiple transportation levels to decentralised additive manufacturing. They suggest that the latter is cheaper in variable costs but may not be so in terms of fixed costs. Deif and ElMaraghy build a system dynamic model to develop approaches that dynamically manage variety and volume decisions for profit maximisation in reconfigurable plug and produce manufacturing systems.

The management of AAMT is not so straightforward. It involves not only knowing the type of AAMT that is appropriate for a particular manufacturing and business situation, but it also includes its specification, integration and use. Therefore, research into these issues remains relevant and necessary. Meanwhile, in the presence of dynamic global business environments and ever-evolving AAMT solutions, it becomes necessary also to upgrade the approach taken towards studying AAMT. A tour into the past serves to remind us about the advanced visions of future manufacturing, which have been promoted decades ahead of their diffusion. We hope that future AAMT research can not only build on previous research but also learn from former and existing research trends.

Sami Farooq, Yang Cheng, Rikke Vestergaard Matthiesen, John Johansen
Center for Industrial Production (CIP), Aalborg University, Denmark
Chris O’Brien
University of Nottingham, Nottingham, UK