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Towards an extended V model to design, test and validate autonomous vehicles: a dialogue with the philosophy of technology.

de Oliveira, L. D. R., Bagno R. B., & Freitas J. S. (2018).  Towards an extended V model to design, test and validate autonomous vehicles: a dialogue with the philosophy of technology.. Gerpisa colloquium.

Towards an extended V model to design, test and validate autonomous vehicles: a dialogue with the philosophy of technology.

 

Introduction

According to Nilsson (2010), Artificial Intelligence (AI) can be defined as an activity involved in making intelligent machines and intelligence can be understood as the capacity of an entity to work properly and with foresight in its environment. The definition given by Nilsson is very generic, but necessary to approach several AI techniques and the contexts in which they are applied. AI applications are already a reality in many economic and industrial sectors and they have a big capacity to generate radical innovations (AZZAN; KHALIL; SAMI, 2017). These innovations can be very challenging to technology developers, users, managers and policy makers. lire la suite

Autonomous cars, from "ownership" to "usage": how autonomous vehicles might corrupt automotive industry's business model

Autonomous Vehicles and the Future of Terrestrial Mobility: a Bibliometric and Integrative Review 

Product-Service System for Autonomous Vehicles: a preliminary typology studies

Knowledge-based assessment applied in Brazilian Toyota plants: employees’ perceptions

Muniz Jr., J., & Ribeiro V. B. (2018).  Knowledge-based assessment applied in Brazilian Toyota plants: employees’ perceptions. Gerpisa colloquium.

1. Introduction
This study aims to propose an assessment tool for Work, Production and Knowledge to support knowledge sharing among blue-collar workers and performance on the shop floor in Brazilian Toyota plants. The analysis evaluates the integrated approach of W, P, K and its factors influencing the labor knowledge sharing and the performance on the shop floor according to the perspectives of employees (blue collar workers), also promoting Nonaka´s knowledge conversion process of Socialization, Externalization, Combination and Internalization (Nonaka, 1994).
Knowledge Management (KM) is the systematic, formal and deliberate action to capture, preserve, share and reuse the tacit and explicit knowledge created and employed by the people during the routine tasks and the improvement of the productive processes, in order to generate measurable results for the organization and for the people (Muniz Jr., Trzeniak and Batista, 2009). Industrial competitiveness presents challenges such as how to encourage employees to work together and share their knowledge even considering layoffs and effective readaptation of the remaining employees to new roles. These challenges are directly related to the trinomial: Work (aspects related to people), Production (physical and productive aspects) and Knowledge (addressing the creation and sharing processes of knowledge). lire la suite

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