Abstract
Entrepreneurs are looking for efficient and effective ways to turn their innovative ideas into marketable products. Due to the lack of accessibility, predictability and agility in the traditional idea-to-market paradigm, stiff hindrances have to be overcome, which is perceived as the manufacturing-entrepreneurship disconnect. Toward bridging this gap, we propose and develop OptiViTh - a decision guidance system to recommend Pareto-optimal instantiation and composition of virtual things - parameterized products and services that can be searched, composed and optimized within a hierarchical service network against customer requirements specs. OptiViTh is based on an extensible and reusable repository of virtual things and their artifacts, which adhere to a proposed mathematical framework. This mathematical framework formalizes the notions of (1) combined product and service designs, (2) customer-facing specifications, (3) requirements specifications, (4) virtual thing search, as a constraint satisfaction problem, (5) compositions of virtual things that are mutually consistent, Pareto-optimal against requirements specifications, and optimal against customer utility function expressed in terms of customer facing metrics, such as cost, delivery terms and desirable product characteristics. We also demonstrate OptiViTh using a case study of cloud-based bicycle production service network combined with its product design.
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Han, X., Brodsky, A. (2023). OptiViTh: A Decision Guidance Framework and System for Design, Analysis and Optimization of Cloud-Manufactured Virtual Things. In: Filipe, J., Śmiałek, M., Brodsky, A., Hammoudi, S. (eds) Enterprise Information Systems. ICEIS 2022. Lecture Notes in Business Information Processing, vol 487. Springer, Cham. https://doi.org/10.1007/978-3-031-39386-0_9
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