Learning and reuse of engineering ramp-up strategies for modular assembly systems

YesWe present a decision-support framework for speeding up the ramp-up of modular assembly systems by learning from past experience. Bringing an assembly system to the expected level of productivity requires engineers performing mechanical adjustments and changes to the assembly process to improve the performance. This activity is time-consuming, knowledge-intensive and highly dependent on the skills of the engineers. Learning the ramp-up process has shown to be effective for making progress faster. Our approach consists of automatically capturing information about the changes made by an operator dealing with disturbances, relating them to the modular structure of the machine and evaluating the resulting system state by analysing sensor data. The feedback thus obtained on applied adaptations is used to derive recommendations in similar contexts. Recommendations are generated with a variant of the k-nearest neighbour algorithm through searching in a multidimensional space containing previous system states. Applications of the framework include knowledge transfer among operators and machines with overlapping structure and functionality. The application of our method in a case study is discussed.Funded by the European Commission as part of the 7th Framework Program under the Grant agreement CP-FP 229208-2, FRAME project

Redistribution and the Nature of Altruism: Should Welfare Programs be Centralized or Decentralized?

Altruism, Redistribution, Centralization, Decentralization, D64, H11, H53, H73,

Decentralizing health services: a new conceptual framework

Decentralization is a central plank of current government health policy. However, it is possible to discern both centralist and decentralist movements in the UK. This paper examines existing frameworks of decentralization in relation to identifying whether policy is decentralist or not and identifies a number of problems that limit their value. Key problems relate to the way decentralization is conceptualized and defined. Existing frameworks are also highly contextualized and are therefore of limited value when applied in different contexts. The paper then presents a new framework which, it is argued, provides a more useful way of examining centralization and decentralization by providing a way of categorizing policies and actions and avoids the problems of being contextually constrained. The paper ends with a discussion of how the framework can be applied in a health context and shows how this framework helps avoid the problems found in previous discussions of decentralization