Innovation processes and industrial districts

In this survey, we examine the operations of innovation processes within industrial districts by exploring the ways in which differentiation, specialization, and integration affect the generation, diffusion, and use of new knowledge in such districts. We begin with an analysis of the importance of the division of labour and then investigate the effects of social embeddedness on innovation. We also consider the effect of forms of organization within industrial districts at various stages of product and process life, and we examine the negative aspects of embeddedness for innovation. We conclude with a discussion of the possible consequences of new information and communications technologies on innovation in industrial districts

Inorganic materials in industrial processes

Although inorganic materials represent a small number to the extreme number of the organic ones, they play a number of crucial roles in several processes of industrial interest. Two significant technologically processes have been selected as “case studies” for this presentation: metallic corrosion and its control, and mitigation of inorganic deposits, both related to industrial water systems.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Bayesian State Space Modeling of Physical Processes in Industrial Hygiene

Exposure assessment models are deterministic models derived from physical-chemical laws. In real workplace settings, chemical concentration measurements can be noisy and indirectly measured. In addition, inference on important parameters such as generation and ventilation rates are usually of interest since they are difficult to obtain. In this paper we outline a flexible Bayesian framework for parameter inference and exposure prediction. In particular, we propose using Bayesian state space models by discretizing the differential equation models and incorporating information from observed measurements and expert prior knowledge. At each time point, a new measurement is available that contains some noise, so using the physical model and the available measurements, we try to obtain a more accurate state estimate, which can be called filtering. We consider Monte Carlo sampling methods for parameter estimation and inference under nonlinear and non-Gaussian assumptions. The performance of the different methods is studied on computer-simulated and controlled laboratory-generated data. We consider some commonly used exposure models representing different physical hypotheses

Collaborative wireless sensor networks in industrial and business processes

Wireless Sensor Networks (WSNs) create the technological basis for building pervasive, large-scale distributed systems, which can sense their environment in great detail, communicate the relevant information via the wireless medium, reason collectively upon the observed situation and react according to the application-specific goals. Embedding sensing, processing and communication in one tiny device (the sensor node or simply mote), which can subsequently collaborate with peers and build a self-organizing, self-healing network, stimulates a long list of applications from various domains, ranging from environmental monitoring to industrial processes, and even further to cognitive robotic systems or space exploration. At first glance the complexity of such applications is overwhelming, given the serious resource limitations of sensor nodes, in terms of computational power, storage space, radio performance and battery power. However, WSNs have a unique feature that balances the inherent resource limitations: the ability of in-network collaboration at scale. Through collaboration WSNs can organize efficiently, prolong system lifetime, handle dynamics, detect and correct errors, all with the final goal of eventually executing reliably the user application. Following this line, researchers devised an impressive number of collaborative WSN algorithms and protocols in recent years. Significant progress has also been made on the market side, so that nowadays we can claim that WSNs are no longer just lab prototypes. Standardization initiatives (such as IEEE 802.15.4) are being put into practice and the general industry trend strongly suggests that the epoch of pioneering research in building and experimenting with “motes” is approaching an end. It is now the logical time for system integration and for creating bridges to connected fields. This thesis focuses on WSN integration in industrial and business processes, and, more specifically, on exploring collaborative techniques to make WSNs more reliable, intelligent, effective and easy-to-use in industry-related scenarios

Analysis of energy use in crisp frying processes

Copyright @ 2010 Politecnico di Bari - BB PressWith increasing energy costs in industrial food frying processes it is essential to identify inefficiencies and minimise them. A way of achieving this is through the application of energy analysis and modelling techniques to characterise the process and investigate the interactions between the various operating and control parameters. The overall objective is to reduce energy consumption without compromising product throughput and quality. This paper provides a review of published work on heat and mass transfer in frying processes. Based on this, a simplified analysis of the key processes has been carried out using an energy balance model. The outputs of this model have been validated using data from an industrial crisp frying facility. The knowledge gained from this validation will be used to better understand and appreciate the energy flows in industrial frying processes and should lead to identification of losses and opportunities for energy recovery.The authors would like to acknowledge the financial support from the UK Engineering and Physical Sciences Research Council (EPSRC), Grant NO. EP/G059799/1, for this project as well as the input from the industrial collaborators and academic collaborators from the Universities of Newcastle and Northumbria

Development of robots and application to industrial processes

An algorithm is presented for using a robot system with a single camera to position in three-dimensional space a slender object for insertion into a hole; for example, an electrical pin-type termination into a connector hole. The algorithm relies on a control-configured end effector to achieve the required horizontal translations and rotational motion, and it does not require camera calibration. A force sensor in each fingertip is integrated with the vision system to allow the robot to teach itself new reference points when different connectors and pins are used. Variability in the grasped orientation and position of the pin can be accomodated with the sensor system. Performance tests show that the system is feasible. More work is needed to determine more precisely the effects of lighting levels and lighting direction

Waste heat utilization in industrial processes

A survey is given of new developments in heat exchangers and heat pumps. With respect to practical applications, internal criteria for plant operation are discussed. Possibilities of government support are pointed out. Waste heat steam generators and waste heat aggregates for hot water generation or in some cases for steam superheating are used. The possibilities of utilization can be classified according to the economic improvements and according to their process applications, for example, gascooling. Examples are presented for a large variety of applications

125th anniversary review: fuel alcohol: current production and future challenges

Global research and industrial development of liquid transportation biofuels are moving at a rapid pace. This is mainly due to the significant roles played by biofuels in decarbonising our future energy needs, since they act to mitigate the deleterious impacts of greenhouse gas emissions to the atmosphere that are contributors of climate change. Governmental obligations and international directives that mandate the blending of biofuels in petrol and diesel are also acting as great stimuli to this expanding industrial sector. Currently, the predominant liquid biofuel is bioethanol (fuel alcohol) and its worldwide production is dominated by maize-based and sugar cane-based processes in North and South America, respectively. In Europe, fuel alcohol production employs primarily wheat and sugar beet. Potable distilled spirit production and fuel alcohol processes share many similarities in terms of starch bioconversion, fermentation, distillation and co-product utilisation, but there are some key differences. For example, in certain bioethanol fermentations, it is now possible to yield consistently high ethanol concentrations of ~20% (v/v). Emerging fuel alcohol processes exploit lignocellulosic feedstocks and scientific and technological constraints involved in depolymerising these materials and efficiently fermenting the hydrolysate sugars are being overcome. These so-called secondgeneration fuel alcohol processes are much more environmentally and ethically acceptable compared with exploitation of starch and sugar resources, especially when considering utilisation of residual agricultural biomass and biowastes. This review covers both first and second-generation bioethanol processes with a focus on current challenges and future opportunities of lignocellulose-to-ethanol as this technology moves from demonstration pilot-plants to full-scale industrial facilities