Ono: an open platform for social robotics

In recent times, the focal point of research in robotics has shifted from industrial ro- bots toward robots that interact with humans in an intuitive and safe manner. This evolution has resulted in the subfield of social robotics, which pertains to robots that function in a human environment and that can communicate with humans in an int- uitive way, e.g. with facial expressions. Social robots have the potential to impact many different aspects of our lives, but one particularly promising application is the use of robots in therapy, such as the treatment of children with autism. Unfortunately, many of the existing social robots are neither suited for practical use in therapy nor for large scale studies, mainly because they are expensive, one-of-a-kind robots that are hard to modify to suit a specific need. We created Ono, a social robotics platform, to tackle these issues. Ono is composed entirely from off-the-shelf components and cheap materials, and can be built at a local FabLab at the fraction of the cost of other robots. Ono is also entirely open source and the modular design further encourages modification and reuse of parts of the platform

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

Problem solving and the co-ordination of innovative activities

In the context of increasingly globalized markets, ever more complex supply chains and international manufacturing networks, corporate decision-making processes involve more and more actors, variables and criteria. This is a challenge for corporate head quarters. Many have argued that the role once attributed to the integrated innovative organisation and its R&D laboratories is increasingly associated with the functioning of networks of specialised innovators. The aim of this paper is to argue that the role of large firms may have changed, but it is far from disappeared. It looks at the interplay of increasing knowledge specialisation, the development of products of increasing complexity that perform a widening range of functionalities, and the emergence and diffusion of new design strategies for both products and organisations, namely modularity. The emergence of modularity as a product and organisational design strategy is clearly connected to recent trends in organisational design. Modularity would allow the decoupling of complex artifacts into simpler, self-contained modules. Each module would, at the extreme, become the sole business of a specialised trade. This paper builds upon the idea that there are cognitive limits to this process of modularisation: what kinds of problems firms solve, and how they solve them, set limits to the extent of division of labour among firms. We draw implications of such limits for both management and economic theory.large firms, knowledge specialisation, complex products, modularity,

Virtual sector profiles for innovation sharing in process industry : sector 01: chemicals

Production data in process industry are proprietary to a company since they are key to the process design and technology expertise. However, data confidentiality restrains industry from sharing results and advancing developments in and across process sectors. Using virtual profiles that simulate the typical operating modes of a given process industry offers an elegant solution for a company to share information with the outside world. This paper proposes a generic methodology to create sector blueprints and applies it to the chemicals industry. It details the profile of a typical chemical site based on essential units and realistic data gathered from existing refineries and chemical plants

Illinois Technograph v. 078, iss. 6 Mar. 1963

published or submitted for publicatio

Growing Ohio's Green Energy Economy

Provides an overview of the state's solar, wind, biomass, and geothermal energy and fuel cell industries and assesses their economic contribution and potential for growth. Recommends policies to encourage further green energy development and job creation

SciTech News Volume 71, No. 2 (2017)

Columns and Reports From the Editor 3 Division News Science-Technology Division 5 Chemistry Division 8 Engineering Division 9 Aerospace Section of the Engineering Division 12 Architecture, Building Engineering, Construction and Design Section of the Engineering Division 14 Reviews Sci-Tech Book News Reviews 16 Advertisements IEEE