Training: an inhibitor of innovation in the automotive supply chain?

Have training programmes become the new Taylorism: allowing OEMs to exercise control over their smaller suppliers and unconsciously preventing these SMEs from innovating, diversifying and growing to become competitive rivals? At the Lisbon Council in March 2000, European government leaders set themselves the target of making the European Union the “most competitive and dynamic knowledge-based economy in the world, capable of sustained economic growth …” within ten years. Human resources are central to the creation and transmission of knowledge and a determining factor in the European automotive industry's potential for innovation. This research seeks to clarify whether the new skills that are being promoted across the supply chain are truly enablers for competitiveness and innovation. As currently practised they may be providing a less effective response to the Lisbon Agenda, i.e. increasing the distribution of skills without the depth that allows companies to become potentially innovative. For SMEs to be encouraged to grow, to be innovative and so be truly competitive, they need training support. The training may be designed just to tackle short term skills needs. It may be designed to instil the demonstrable best practice of its customer and lean manufacturing is an eminent example of this type. Training must also be designed in the context of where the SME aspires to be, to allow the SME to mature and develop. This research has highlighted the risk when externally promoted and funded training potentially constrains the potential for innovation and the Lisbon goals.Peer reviewe

The evolution of bits and bottlenecks in a scientific workflow trying to keep up with technology: Accelerating 4D image segmentation applied to nasa data

In 2016, a team of earth scientists directly engaged a team of computer scientists to identify cyberinfrastructure (CI) approaches that would speed up an earth science workflow. This paper describes the evolution of that workflow as the two teams bridged CI and an image segmentation algorithm to do large scale earth science research. The Pacific Research Platform (PRP) and The Cognitive Hardware and Software Ecosystem Community Infrastructure (CHASE-CI) resources were used to significantly decreased the earth science workflow's wall-clock time from 19.5 days to 53 minutes. The improvement in wall-clock time comes from the use of network appliances, improved image segmentation, deployment of a containerized workflow, and the increase in CI experience and training for the earth scientists. This paper presents a description of the evolving innovations used to improve the workflow, bottlenecks identified within each workflow version, and improvements made within each version of the workflow, over a three-year time period

New Hampshire University Research and Industry Plan: A Roadmap for Collaboration and Innovation

This University Research and Industry plan for New Hampshire is focused on accelerating innovation-led development in the state by partnering academia’s strengths with the state’s substantial base of existing and emerging advanced industries. These advanced industries are defined by their deep investment and connections to research and development and the high-quality jobs they generate across production, new product development and administrative positions involving skills in science, technology, engineering and math (STEM)