Identification of the value proposition of an evolvable production system

Abstract

Current production paradigms and related biases concerning automation are an obstacle for the technological development and subsequent application of intelligent assembly solutions such as the automation based on the evolvable paradigm. A deeper understanding of the potential behind such technology is a fundamental step towards a proficient industrial embodiment. The concept of Value Proposition can be used as a holistic analytical tool able to support a full characterization of the appeal that such technology has on the assembly automation market. The two dimensional bottom-up approach proposed in this work allows the identification and description of six potential value offerings connected with an Evolvable Assembly system, which in turn pave the way to more efficient business models.

Modelling of secondary cooling system with a distributed architecture, using Coloured Petri nets

“…However, a correct definition of distributed structure demands several challenges to be overcome, such as the availability of specialized resources, integration methods for the modules, coordination of treatment information centres, reliability, security, and increased dynamic of systems [4]. Thus, this study addressed the issue of an adequate specification of a distributed PS using a formal tool, such as: Coloured Petri Nets (CPN).…”

Characterization of Costs and Strategies for Automation in Evolvable Production Systems

“…Conceiving and developing EPS needs sound economical and operational characterization in order to trigger and support the necessary investments [5]. This paper proposes a first step into this rather large and heterogeneous knowledge gap.…”

“…In recent years, the active EPS research community has extensively studied different aspects of such domain which, in turn has spread in different directions through a large amount of heterogeneous contributions: research requirements [10], design support tools and models [11,12], business processes [5,13,14], diagnostic [15,16], system deployment and description [17,18], system configuration [19], self-learning mechanisms [20], self-organization theory [21] and management of complexity [22] among the others. Most of the research efforts that shaped the EPS paradigm at the early stage have been carried out within the large collaborative European project EUPASS [23] while the more recent developments have been attained within the following European project IDEAS [24,25].…”