#5428. Benefiting from additive manufacturing for mass customization across the product life cycle

August 2026publication date
Proposal available till 15-05-2025
4 total number of authors per manuscript0 $

The title of the journal is available only for the authors who have already paid for
Journal’s subject area:
Statistics and Probability;
Control and Optimization;
Strategy and Management;
Management Science and Operations Research;
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More details about the manuscript: Science Citation Index Expanded or/and Social Sciences Citation Index
Abstract:
Additive manufacturing (AM) was initially designed for prototyping and product personalization, where high production quantities were not required. Now, it is also implemented for final part production to achieve cost-effective mass customization (MC). Thanks to its tool-less production and extreme flexibility, AM has the potential to address individual customer preferences with custom final parts. Nevertheless, despite its increased competitiveness, AM is not yet likely to replace traditional MC systems, but it can complement them, improving manufacturing efficiency. To broaden our understanding of how AM can complement traditional manufacturing systems, we develop an exploratory quantitative model. First, we leverage customer-centricity in a novel time-varying locational choice model of heterogeneous customers, coupling the Bass and the Hotelling–Lancaster models. Then, we investigate customer-centric marketing and operations decisions, exploring technology-switching scenarios that interchange AM with MC across the product life cycle (PLC). We formulate and solve an optimization problem by jointly deciding on technology-switching times, pricing, and product variety strategies to maximize a manufacturers profit and meet individual customers’ diverse and evolving needs. We use a validated Sample Average Approximation approach for the numerical solution of our non-convex optimization problem. Testing different pricing strategies, we show that decreasing and flexible trajectories are optimal. We derive analytical properties for the optimal pricing policy and demonstrate that a manufacturer can benefit from interchanging AM and MC across the PLC, in particular by adopting an AM-MC-AM scenario.
Keywords:
Additive manufacturing; Customer preference; Mass customization; Pricing; Switching time

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