Analysis of barriers to implement additive manufacturing technology in the Indian automotive sector

Abstract

Purpose A spurt in the usage of additive manufacturing (AM) is observed in industrial applications to produce final parts along with rapid prototyping and rapid tooling. Despite the potential benefits of on-demand and on-location production of customised or complex shape parts, widespread implementation of this disruptive production technology is not yet visible. The purpose of this paper is to examine the various barriers to implement AM in the Indian automotive sector and analyse interrelations among them. Design/methodology/approach Based on the extant literature and discussions with industry experts, ten major barriers are identified. The authors use a modified Fuzzy interpretive structural modelling (Fuzzy-ISM) method to derive strengths of relationships among these barriers, develop hierarchical levels, and thereafter group and rank these barriers. Findings ISM diagraph is developed to demonstrate how the barriers drive one another. Production technology capabilities and government support emerge as the most critical factors, with high driving power and medium dependence. Research limitations/implications While identified barriers may be similar across the automotive industry, generalisation of results for interrelationships and ranks in other industries may be limited. Practical implications The findings may be useful to managers to develop suitable mitigation strategies, and take more informed decisions, with individual focus, level focus or cluster focus. Social implications Findings clearly establish that the role of management and government is crucial in mitigating workers’ resistance to AM implementation. Originality/value This paper contributes to AM literature by the structured presentation of the barriers to implement AM in the Indian automotive sector. It also extends the Fuzzy-ISM method by presenting calculation of indirect relations using the appropriate max-product composition and in ranking the barriers.

Additive manufacturing: empirical evidence for supply chain integration and performance from the automotive industry

“…For suppliers, supply chain performance concerns a producer's perception of its own suppliers in terms of quality, flexibility, delivery, and the like (Huo, 2012). In principle, Additive Manufacturing offers much support for supply chain performance as it promotes rapid innovation and product modifications (Dwivedi et al, 2017), together with quick changes in design (Chan et al, 2018). Through AM total delivery time can be reduced (Weller et al, 2015), and additional costs of part complexity and variability are significantly lower than in traditional manufacturing (Simhambhatla and Karunakaran, 2015).…”

“…Again, the Additive Manufacturing literature highlights several attributes of the technologies which may positively contribute to supply chain performance in the automotive sector. This includes accelerated product development with reduced time-to-market (Dwivedi et al, 2017;Giffi et al, 2014), increased product differentiation (Chan et al, 2018), and faster order fulfillment (Sasson and Johnson, 2016 Aside from the supplier and customer-oriented performance, supply chain performance is often considered in terms of cost, reliability, and time performance measures. Compared to traditional approaches to manufacturing, Additive Manufacturing is typically more economical at lower production volumes thanks to the elimination of constraints such as tooling (Wohlers, 2016), but has also been identified as offering benefits to the automotive supply chain in the reduction of material usage (Gao et al, 2015), lower warehousing and transportation costs (Sasson and Johnson, 2016), and decreased inventory holding costs (Dwivedi et al, 2017) which are enabled through on-demand production.…”

“…The 'digital' nature of Additive Manufacturing technologies in terms of design and production are expected to promote integration between processes and functions within an automotive manufacturer. For example, Dwivedi et al (2017) suggest Additive Manufacturing promotes the concept of digital inventory to meet demand inside factories, whilst Prajogo et al (2018) identify Additive Manufacturing as improving data flow between departments. Focusing specifically on integration, Dalenogare et al (2018) Whilst internal integration focuses on the 'internal chain' it is also important to consider customer and supplier integration.…”

“…For the supply chain, Additive Manufacturing has the potential to enable enormous changes (Candi and Beltagui, 2019;Christopher and Ryals, 2014;Holmström and Partanen, 2014;Waller and Fawcett, 2014), but as-yet there is notably little consensus in the literature over what will be achieved, and a severe lack of empirical evidence on which conclusions may be drawn. One of the most popular applications for Additive Manufacturing is within the automotive industry (Wohlers, 2016), as it promises innovations in product development (Giffi et al, 2014) and significant financial savings by simplifying the long and complex supply chains (Dwivedi et al, 2017). In automotive industries, the huge variety and complexity of products often leads to Original Equipment Manufacturers (OEMs) outsourcing many activities in product design and manufacture to specialist suppliers, helping to simplify internal processes and minimize costs (Gobetto, 2014).…”

Modelling of an Additive 3D-Printing Process Based on Design of Experiments Methodology

“…This is the biggest reason that AM is favoured in this sector, but there are many other reasons to apply this technology in this sector as well: AM can be used to produce light parts, complex shapes and digital parts, and can reduce the cost of production because it does not produce the same parts required by conventional manufacturing processes (Lipson et al, 2012). In the automotive sector, AM was also used to produce parts, but most manufacturers decided not to pursue this technology for the mass production of automobiles due to the high cost of production (Dwivedi, Srivastava and Srivastava, 2015).…”