Improving the design process for factories:modelling human performance variation

Theprocess of manufacturing system design frequently includes modeling, and usually, this means applying a technique such as discrete event simulation (DES). However, the computer tools currently available to apply this technique enable only a superficial representation of the people that operate within the systems. This is a serious limitation because the performance of people remains central to the competitiveness of many manufacturing enterprises. Therefore, this paper explores the use of probability density functions to represent the variation of worker activity times within DES models.

Human performance modelling as an aid in the process of manufacturing system design

Manufacturing system design is an ongoing activity within industry. Modelling tools based on Discrete Event Simulation are often used by practitioners during this design cycle. However, such tools do not adequately model the behaviour of 'direct' workers in manufacturing environments. There is an important need to expand the capability of modelling to include the relationships between human centred factors (demography, attitudes, beliefs, etc), their working environment (physical and organizational), and their subsequent performance in terms of productive routines. Therefore, this paper describes research that has formed a pilot modelling methodology that is an important first step in providing such a capability.

Human performance modelling as an aid to manufacturing system design

Once the factory worker was considered to be a necessary evil, soon to be replaced by robotics and automation. Today, many manufacturers appreciate that people in direct productive roles can provide important flexibility and responsiveness, and so significantly contribute to business success. The challenge is no longer to design people out of the factory, but to design factory environment that help to get the best performance from people. This paper describes research that has set out to help to achieve this by expanding the capabilities of simulation modeling tools currently used by practitioners.

Using architecture models to support the generation and operation of component-based adaptive systems

Modelling architectural information is particularly important because of the acknowledged crucial role of software architecture in raising the level of abstraction during development. In the MDE area, the level of abstraction of models has frequently been related to low-level design concepts. However, model-driven techniques can be further exploited to model software artefacts that take into account the architecture of the system and its changes according to variations of the environment. In this paper, we propose model-driven techniques and dynamic variability as concepts useful for modelling the dynamic fluctuation of the environment and its impact on the architecture. Using the mappings from the models to implementation, generative techniques allow the (semi) automatic generation of artefacts making the process more efficient and promoting software reuse. The automatic generation of configurations and reconfigurations from models provides the basis for safer execution. The architectural perspective offered by the models shift focus away from implementation details to the whole view of the system and its runtime change promoting high-level analysis. © 2009 Springer Berlin Heidelberg.

Design and evaluation of a framework for cooperative and adaptive QoS control of DSRC network for road safety applications

Dedicated short-range communications (DSRC) are a promising vehicle communication technique for collaborative road safety applications (CSA). However, road safety applications require highly reliable and timely wireless communications, which present big challenges to DSRC based vehicle networks on effective and robust quality of services (QoS) provisioning due to the random channel access method applied in the DSRC technique. In this paper we examine the QoS control problem for CSA in the DSRC based vehicle networks and presented an overview of the research work towards the QoS control problem. After an analysis of the system application requirements and the DSRC vehicle network features, we propose a framework for cooperative and adaptive QoS control, which is believed to be a key for the success of DSRC on supporting effective collaborative road safety applications. A core design in the proposed QoS control framework is that network feedback and cross-layer design are employed to collaboratively achieve targeted QoS. A design example of cooperative and adaptive rate control scheme is implemented and evaluated, with objective of illustrating the key ideas in the framework. Simulation results demonstrate the effectiveness of proposed rate control schemes in providing highly available and reliable channel for emergency safety messages. © 2013 Wenyang Guan et al.

Fully probabilistic control design in an adaptive critic framework

Optimal stochastic controller pushes the closed-loop behavior as close as possible to the desired one. The fully probabilistic design (FPD) uses probabilistic description of the desired closed loop and minimizes Kullback-Leibler divergence of the closed-loop description to the desired one. Practical exploitation of the fully probabilistic design control theory continues to be hindered by the computational complexities involved in numerically solving the associated stochastic dynamic programming problem. In particular very hard multivariate integration and an approximate interpolation of the involved multivariate functions. This paper proposes a new fully probabilistic contro algorithm that uses the adaptive critic methods to circumvent the need for explicitly evaluating the optimal value function, thereby dramatically reducing computational requirements. This is a main contribution of this short paper.

Adaptive E-learning Content Design and Delivery Based on Learning Styles and Knowledge Level

ACM Computing Classification System (1998): K.3.1, K.3.2.

Adaptive evolution of a key phytoplankton species to ocean acidification

Ocean acidification, the drop in seawater pH associated with the ongoing enrichment of marine waters with carbon dioxide from fossil fuel burning, may seriously impair marine calcifying organisms. Our present understanding of the sensitivity of marine life to ocean acidification is based primarily on short-term experiments, in which organisms are exposed to increased concentrations of CO2. However, phytoplankton species with short generation times, in particular, may be able to respond to environmental alterations through adaptive evolution. Here, we examine the ability of the world's single most important calcifying organism, the coccolithophore Emiliania huxleyi, to evolve in response to ocean acidification in two 500-generation selection experiments. Specifically, we exposed E. huxleyi populations founded by single or multiple clones to increased concentrations of CO2. Around 500 asexual generations later we assessed their fitness. Compared with populations kept at ambient CO2 partial pressure, those selected at increased partial pressure exhibited higher growth rates, in both the single- and multiclone experiment, when tested under ocean acidification conditions. Calcification was partly restored: rates were lower under increased CO2 conditions in all cultures, but were up to 50% higher in adapted compared with non-adapted cultures. We suggest that contemporary evolution could help to maintain the functionality of microbial processes at the base of marine food webs in the face of global change.

Design concept evaluation based on rough number and information entropy theory

Concept evaluation at the early phase of product development plays a crucial role in new product development. It determines the direction of the subsequent design activities. However, the evaluation information at this stage mainly comes from experts' judgments, which is subjective and imprecise. How to manage the subjectivity to reduce the evaluation bias is a big challenge in design concept evaluation. This paper proposes a comprehensive evaluation method which combines information entropy theory and rough number. Rough number is first presented to aggregate individual judgments and priorities and to manipulate the vagueness under a group decision-making environment. A rough number based information entropy method is proposed to determine the relative weights of evaluation criteria. The composite performance values based on rough number are then calculated to rank the candidate design concepts. The results from a practical case study on the concept evaluation of an industrial robot design show that the integrated evaluation model can effectively strengthen the objectivity across the decision-making processes.

Propuesta sostenible para mitigar los efectos climáticos adversos en una ciudad costera de Argentina

Los indicadores de sostenibilidad climática constituyen herramientas fundamentales para complementar las políticas de ordenamiento del territorio urbano y pueden beneficiar la calidad de vida sus habitantes. En el presente trabajo se diseñó un indicador climático urbano para la ciudad de Bahía Blanca considerando variables meteorológicas y análisis de la percepción social. El mismo permitió delimitar la ciudad en cuatro regiones bien diferenciadas entre sí. A partir de entonces, se realizó una propuesta sostenible para mitigar los efectos adversos del clima a partir de la aplicación del método DPSIR. Las mismas estuvieron destinadas a mejorar las condiciones de vida de la población. Los resultados permitieron considerar que una pronta implementación de la misma junto con una activa participación de los actores sociales y los tomadores de decisiones es necesaria para mejorar las condiciones actuales en la que se encuentra la ciudad. Con las medidas propuestas, la población local sabrá cómo actuar ante la ocurrencia de distintos eventos extremos, eventos de desconfort climático, etc. Al ser un método sencillo, la metodología aplicada en este estudio puede replicarse en otras ciudades del mundo con el objetivo de mejorar la calidad de vida de los habitantes.

The evolution of public–private partnership in Ireland: a sustainable pathway?

Ireland is a latecomer to Public Private Partnership (PPP) having only adopted it in 1998. Prior to the credit crisis, Ireland followed the UK model with PPPs being implemented in transport, education, housing/urban regeneration and water/wastewater. Having stalled during the credit crisis, PPP has been reactivated recently with the domestic infrastructure stimulus programme . The focus of this paper is on Ireland as a younger participant in PPP and the nexus between adoption patterns and sustainability characteristics of Irish PPP. Using document analysis and exploratory interviews, the paper examines the reasons for Ireland’s interest in PPP which cannot be attributed to economic rationales alone. We consider three explanations: voluntary adoption – where the UK model was closely followed as part of a domestic modernisation agenda; coercive adoption – where PPP policy was forced upon public sector organisations; and institutional isomorphism – where institutional creation and change around PPP was promoted to help public sector organisations gain institutional legitimacy. We find evidence of all three patterns with coercive adoption becoming more relevant in recent years, which is likely to affect sustainability adversely unless incentives for voluntary adoption are strengthened and institutional capacity building is boosted.

Sustainability Enhancement of a Turbine Vane Manufacturing Cell through Digital Simulation based Design

Modern manufacturing systems should satisfy emerging needs related to sustainable development. The design of sustainable manufacturing systems can be valuably supported by simulation, traditionally employed mainly for time and cost reduction. In this paper, a multi-purpose digital simulation approach is proposed to deal with sustainable manufacturing systems design through Discrete Event Simulation (DES) and 3D digital human modelling. DES models integrated with data on power consumption of the manufacturing equipment are utilized to simulate different scenarios with the aim to improve productivity as well as energy efficiency, avoiding resource and energy waste. 3D simulation based on digital human modelling is employed to assess human factors issues related to ergonomics and safety of manufacturing systems. The approach is implemented for the sustainability enhancement of a real manufacturing cell of the aerospace industry, automated by robotic deburring. Alternative scenarios are proposed and simulated, obtaining a significant improvement in terms of energy efficiency (−87%) for the new deburring cell, and a reduction of energy consumption around −69% for the coordinate measuring machine, with high potential annual energy cost savings and increased energy efficiency. Moreover, the simulation-based ergonomic assessment of human operator postures allows 25% improvement of the workcell ergonomic index.