Production planning of multi-stage multi-option seru production systems with sustainable measures

With the concerns over climate change and the escalation in worldwide population, sustainable development attracts more and more attention of academia, policy makers, and businesses in countries. Sustainable manufacturing is an inextricable measure to achieve sustainable development since manufacturing is one of the main energy consumers and greenhouse gas contributors. In the previous researches on production planning of manufacturing systems, environmental factor was rarely considered. This paper investigates the production planning problem under the performance measures of economy and environment with respect to seru production systems, a new manufacturing system praised as Double E (ecology and economy) in Japanese manufacturing industries. We propose a mathematical model with two objectives minimizing carbon dioxide emission and makespan for processing all product types by a seru production system. To solve this mathematical model, we develop an algorithm based on the non-dominated sorting genetic algorithm II. The computation results and analysis of three numeral examples confirm the effectiveness of our proposed algorithm. © 2014 Elsevier Ltd. All rights reserved.

Modelling and control of nonlinear systems using Gaussian processes with partial model information

Gaussian processes are gaining increasing popularity among the control community, in particular for the modelling of discrete time state space systems. However, it has not been clear how to incorporate model information, in the form of known state relationships, when using a Gaussian process as a predictive model. An obvious example of known prior information is position and velocity related states. Incorporation of such information would be beneficial both computationally and for faster dynamics learning. This paper introduces a method of achieving this, yielding faster dynamics learning and a reduction in computational effort from O(Dn2) to O((D - F)n2) in the prediction stage for a system with D states, F known state relationships and n observations. The effectiveness of the method is demonstrated through its inclusion in the PILCO learning algorithm with application to the swing-up and balance of a torque-limited pendulum and the balancing of a robotic unicycle in simulation. © 2012 IEEE.

A matter of life and death: sociomateriality, information systems and critical care

Sociomateriality has been attracting growing attention in the Organization Studies and Information Systems literatures since 2007, with more than 140 journal articles now referring to the concept. Over 80 percent of these articles have been published since January 2011 and almost all cite the work of Orlikowski (2007, 2010; Orlikowski and Scott 2008) as the source of the concept. Only a few, however, address all of the notions that Orlikowski suggests are entailed in sociomateriality, namely materiality, inseparability, relationality, performativity, and practices, with many employing the concept quite selectively. The contribution of sociomateriality to these literatures is, therefore, still unclear. Drawing on evidence from an ongoing study of the adoption of a computer-based clinical information system in a hospital critical care unit, this paper explores whether the notions, individually and collectively, offer a distinctive and coherent account of the relationship between the social and the material that may be useful in Information Systems research. It is argued that if sociomateriality is to be more than simply a label for research employing a number of loosely related existing theoretical approaches, then studies employing the concept need to pay greater attention to the notions entailed in it and to differences in their interpretation.

Towards measuring the impact of information availability on maintenance decisions

Decisions concerning maintenance have become increasingly important and requires a diverse set of information as systems become more complex. The availability of information has an impact on the effectiveness of these decisions, and thus on the performance of the asset. This paper highlights the importance of quantifying the value of information on maintenance decisions and asset performance. In particular, we emphasise the need to focus on measuring value as opposed to cost of maintenance, which is the current practice. In this direction, we propose a measure - Value of Ownership (VOO) - to assess the value of information and performance of maintenance decisions throughout an assets lifecycle. © 2009 IFAC.