By Gaetano Cascini
This publication constitutes the refereed complaints of theIFIP WG 5.4/TC 5 Second Topical consultation on Computer-Aided Innovation held at the 20 th international desktop Congress in Milano, Italy on September 7-10, 2008. The IFIP sequence publishes state of the art leads to the sciences and applied sciences of data and conversation. The scope of the sequence comprises: foundations of desktop technological know-how; software program thought and perform; schooling; computing device functions in expertise; conversation platforms; structures modeling and optimization; details platforms; pcs and society; desktops know-how; protection and defense in details processing platforms; synthetic intelligence; and human-computer interplay. court cases and post-proceedings of refereed foreign meetings in laptop technology and interdisciplinary fields are featured. those effects frequently precede magazine e-book and symbolize the most up-tp-date learn. The crucial target of the IFIP sequence is to motivate schooling and the dissemination and alternate of data approximately all elements of computing.
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Extra info for Computer-Aided Innovation (CAI): IFIP 20th World Computer Congress, Proceedings of the Second Topical Session on Computer-Aided Innovation, WG 5.4 TC 5 ... Federation for Information Processing)
Input data which can be acquired during the simulation are: • numerical manikin body information (angles and postures); • task and single movement times. The Computer Aided Innovation consists in using both posture recognition and all ergonomic evaluation tools within a Product-Process-Resources (PPR) data Methodology development of human task simulation 25 collaboration system, that’s ensuring that human factors become an intuitive component in the manufacturing design process, so having several advantages: • to improve simulation reliability: experts are supported, in real time, during the simulation because they can define the best movement for the worker, cutting down or changing incongruous postures; • to improve the analysis performance: according to analyzed task, the expert can evaluate the most meaningful index between all the available ones; • to ensure conformance to relevant health and safety standards; • to reduce analysis time: critical postures are recognized at once, reducing subjective interpretations; • to accelerate time to market; • to reduces design timeframe and associated costs.
Cascini and M. Zini patent. Figure 2 shows a portion of the citation tree related to the former patent: each arrow represents a backward citation. In order to perform such an evolutionary analysis each patent has been analyzed by a technician and a summary has been extracted in the form ProblemSolution (figure 2, close up). In other words, the citation trees have been manually translated into a Problem-Solution tree which can be used with similar purposes of the OTSM-TRIZ Problem Flow Network proposed in .
It is worth to notice that the score assigned to the components of each invention allows to select a subset of sentences from the description and the claims of the patent where the top-ranked components are mentioned. In  it was demonstrated that such a subset of sentences is sufficient for a “person skilled in the art” for understanding what the core of the patent is about. In this paper, the top-ranked components and their hierarchical and functional relationships are adopted as a means to compare the inventions of a given project in order to estimate their similarity, as described in the following paragraph.
Computer-Aided Innovation (CAI): IFIP 20th World Computer Congress, Proceedings of the Second Topical Session on Computer-Aided Innovation, WG 5.4 TC 5 ... Federation for Information Processing) by Gaetano Cascini