Brief review of Mass Customisation Classifications Andrew Lyons1, Dong Li1, Jorge Hernandez1, Lucy Everington1, e‐Business & Supply Chain Management Research Centre Technology & Innovation. 1 Management School. University of Liverpool (UK) 1.‐ Overview In this work the main classification system used has been taken from Poulin M, Montreuil B and Martel A 2006 ‘Implications of personalization offers on demand and supply network design: A case from the golf club industry.’ There are several reasons for this. Firstly the Poulin et al is more subtle, more nuanced and makes more finely grained distinctions between mass customisation schemas than other mass customisation classification systems, making it easier to fit a network type to each one. Secondly Poulin et al (2006) and Montreuil and Poulin (2005) provided the most comprehensive information on how the authors envisioned networks for each level of the classification system would be constructed. These papers provided the foundations for the networks models used in this conceptual model. Although these categories were original meant to refer to personalisation rather than mass customisation, it could be extrapolated that since these categories were adapted from a mass customisation set (Lampel and Minzberg 1991) it is possible to use them as mass customisation networks. Table 1 shows the eight levels defined by Poulin et al. The other often cited customisation classification sets were considered to see if there was anything potentially missing from the Poulin et al set. Table 2 shows how the Poulin et al set related to other commonly cited classifications. 1/4 Table 1: Personalisation framework (Poulin et al 2006.) Personalisation option 1. Popularising 2. Varietising 3. Accessorising 4. Parametering 5. Tailoring 6. Adjusting 7. Monitoring 8. Collaborating Characteristics Limited number of products to match a wide variety of customer needs, for those who want off‐the‐shelf products. Focus on evolving the popular product mix in line with evolving customer needs. Extensive mix of products to satisfy almost all customer needs. Retailers pick those they want to offer off‐the‐shelf and rely on quick delivery from the distribution network for fast delivery of the others. A limited set of core products matched with a wide array of accessories. Final assembly of accessorized products performed to order either by the user, the retailer or a fulfilment centre. Customer defines the desired product through the setting of parameters and the selection of options. He is guided through the specification process. Manufacturing is strictly to order. Product designed/engineered to customer needs. The customer is closely involved in the product realization process. Product adjusted to customer needs after usage. Distributed information systems capture customer feedback. (SIC) Product is replaced by more adequate product as the customer needs evolve, ensuring continually a best‐fit product. This involves regular and interactive customer feedback Client is viewed as a collaborator with an open dialogue. Expert field systems interact with clients, seeking to continually optimize client return 2/4 Table 2: Comparison of Mass Customisation Classifications Networks adapted from M Poulin et al 2006 Da Silveira et al 2001 (used by wp2) Lampel and Mintzberg 1991 (used by Poulin) Duray et al 2000 Order fulfilment Strategy 1 Popularising Level 2: Usage Pure standardisation Build to stock (product customised by user) 2 Varietising Level 1: Standardisation Segmented Standardisation Build to stock 3 Accessorising Level 3: Packaging and distribution Level 5+4: Additional custom work/service Level 6: Assembly Customised Standardisation Assemblers Assemble to order 4 Parametering Level 7: Fabrication Tailored Customisation Modularizers Make to order 5 Tailoring Level 7: Fabrication Tailored Customisation Involvers Make to order 6 Adjusting Level 8: Design Pure Customisation Fabricators Design to order 7 Monitoring Level 8: Design Pure Customisation Fabricators Design to order 9 Collaborating Level 8: Design Pure Customisation Fabricators Design to order It can be seen from table 2 that the Poulin et al classification system does include all the levels of customisation seen in other commonly cited classification systems. Although the Poulin et al classification system has more levels than the others and therefore splits most of the other classification systems levels into sub levels, accessorising seems to cover four of the Da Silveira et al levels, level 3 packaging and distribution, levels 4+5 additional custom work/service and level 6 assembly. For this reason in the network models this level was split into three network models. The three particular types of accessorising that were identified were 1. When assembly is done at the retailer (level 6 assembly) 2. When assembly is done at the fulfilment and distribution centre (level 3 Packaging and distribution, levels 5+4 additional custom work/service, level 6 assembly) 3/4 3. When assembly is done at the fulfilment and distribution centre but the manufacturer only assembles the parts they do not make any of them (level 6 assembly.) ACKNOWLEDGEMENT FP7 NMP Project “Resilient Multi‐Plant Networks” (www.remplanet.eu). Grant agreement n° NMP2‐SL‐2009‐ 229333. Deliverable D3.2: “Conceptual framework”. REFERENCES DaSilveira G, Borenstein D and Fogliatto F 2001 ‘Mass customisation: Literature Review and research directions’ International Journal of Production Economics vol 72 No 1 pp1‐13 Duray R, Ward P, Milligan G and Berry W 2000 ‘Approaches to mass customisation: configurations and empirical validation’ Journal of Operations Management vol 18 pp605‐ 625 Lampel J and Mintzberg H 1996 ‘Customizing Customization’ Sloan Management Review vol 38 no 1 pp21‐30 Montreuil B and Poulin M 2005 ‘Demand and supply network design scope for personalized manufacturing’ Production Planning and Control Vol 16 No 5 pp454‐469 Poulin M, Montreuil B and Martel A 2005 ‘Implications of personalization offers on demand and supply network design: A case from the golf club industry’ European Journal of Operational Research vol 169 pp996‐1009 4/4
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