How has Japan become a major economic power, a world leader in the automotive and electronics industries? What is the secret of their success? The consensus has been that, though the Japanese are not particularly innovative, they are exceptionally skilful at imitation, at improving products that already exist. But now two leading Japanese business experts, Ikujiro Nonaka and Hiro Takeuchi, turn this conventional wisdom on its head: Japanese firms are successful, they contend, precisely because they are innovative, because they create new knowledge and use it to produce successful products and technologies. Examining case studies drawn from such firms as Honda, Canon, Matsushita, NEC, 3M, GE, and the U.S. Marines, this book reveals how Japanese companies translate tacit to explicit knowledge and use it to produce new processes, products, and services.

The knowledge-creating company : how Japanese companies create the dynamics of innovation

Open Innovation: The New Imperative for Creating and Profiting from Technology

A literature and practice review to develop sustainable business model archetypes

Industry 4.0: A Survey on Technologies, Applications and Open Research Issues

* Starting from Need* Evolution of the Toyota Production System* Further Development* Genealogy of the Toyota Production System* The True Intention of the Ford System* Surviving the Low-Growth Period

Toyota production system : beyond large-scale production

Green Virtual Enterprise Breeding Environments and their Reverse-Green Virtual Enterprises, as dynamic reverse supply networks, represent a promising paradigm to face the reverse logistics and end-of-life manufacturing challenges towards closed-loop industrial processes, closed-loop supply networks and sustainable industrial development models. This paper explores different collaborative product recovery business opportunities and strategies for capturing current missed value at the end-of-lifecycle with new activities, relationships and network configurations, put forward based on the disciplines of Industrial Ecology, Collaborative Networks and Lifecycle Management.

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Reverse – Green Virtual Enterprises and Their Breeding Environments: Closed-Loop Networks

The Industrial Ecology (IE) is a new interdisciplinary field focused on sustainable development. IE aims to the shifting of industrial processes from open-loop systems where different resources move through a system to become wastes to a closed-loop system where wastes become inputs for new processes. This paper introduces a Green Virtual Enterprise (GVE) model as an emerging sustainable manufacturing and logistics mode focused on offering, delivering and recovering green products to/from the market, under a lifecycle thinking and supported by its source network. GVEs creation is considered within a GVE breeding environment context, which acts as a long-term collaborative network aimed at offering the conditions to efficiently promote the sharing and recycling of resources such as: information, materials, water, energy and/or infrastructure with the intention of increasing economic gains and achieving sustainable development.

/pdf/green-virtual-enterprises-and-their-breeding-environments-38ogvs9l7y.pdf

Green Virtual Enterprises and Their Breeding Environments

During October 2009, PRO-VE-IFIP Working Conference on Virtual Enterprises commemorated its 10th Anniversary as a continuous series of successful conferences offering researchers and practitioners ...

Co-innovation and collaborative networks

Closed-circuit television monitoring systems used for surveillance do not provide an immediate response in situations of danger such as armed robbery. In addition, they have multiple limitations when human operators perform the monitoring. For these reasons, a firearms detection system was developed using a new large database that was created from images extracted from surveillance videos of situations in which there are people with firearms. The system is made up of two parts—the “Front End” and “Back End”. The Front End is comprised of the YOLO object detection and localization system, and the Back End is made up of the firearms detection model that is developed in this work. These two systems are used to focus the detection system only in areas of the image where there are people, disregarding all other irrelevant areas. The performance of the firearm detection system was analyzed using multiple convolutional neural network (CNN) architectures, finding values up to 86% in metrics like recall and precision in a network configuration based on VGG Net using grayscale images.

https://www.mdpi.com/2076-3417/9/15/2965/pdf

Convolutional Models for the Detection of Firearms in Surveillance Videos

Nowadays, smart warehouses mostly use Automated Guided Vehicles (AGVs) controlled through magnetic or painted paths. This approach is suitable for “static slotting” warehouses, and for places where humans do not cross paths with mobile robots. Therefore, fixed-path AGVs are not an optimal solution for dynamic slotting “chaotic storage” warehouses, where picking and delivery paths are often changing. Hence, it is important to create an environment where AGVs have planned their path, and storekeepers can see their paths, and mark restricted areas by virtual means if needed, for these mobile robots and humans to move and stand safely around a smart warehouse. In this paper, we have proposed an Augmented Reality (AR) environment for storekeepers, where they can see an AGV planned path, and they can add virtual obstacles and walls to the mobile robots’ cyber-physical navigation view. These virtual obstacles and walls can be used to determine restricted areas for mobile robots, which can be seen for example as safe areas for humans’ and/or robots’ stationary work. Finally, we introduce the system architecture supporting the proposed AR environment for humans-mobile robots safe and productive interaction.

David Romero

Papers

Reverse – Green Virtual Enterprises and Their Breeding Environments: Closed-Loop Networks

Green Virtual Enterprises and Their Breeding Environments

Co-innovation and collaborative networks

Convolutional Models for the Detection of Firearms in Surveillance Videos

Augmented Reality for Humans-Robots Interaction in Dynamic Slotting “Chaotic Storage” Smart Warehouses