Conception of a flexible integrator and lean model for integrated management systems

Management systems standards (MSSs) have developed in an unprecedented manner in the last few years. These MSS cover a wide array of different disciplines, aims and activities of organisations. Also, organisations are populated with an enormous diversity of independent management systems (MSs). An integrated management system (IMS) tends to integrate some or all components of the business. Maximising their integration in one coherent and efficient MS is increasingly a strategic priority and constitutes an opportunity for businesses to be more competitive and consequently, promote its sustainable success. Those organisations that are quicker and more efficient in their integration and continuous improvement will have a competitive advantage in obtaining sustainable value in our global and competitive business world. Several scholars have proposed various theoretical approaches regarding the integration of management sub-systems, leading to the conclusion that there is no common practice for all organisations as they encompass different characteristics. One other author shows that several tangible and intangible gains for organisations, as well as to their internal and external stakeholders, are achieved with the integration of the individual standardised MSs. The purpose of this work was to conceive a model, Flexible, Integrator and Lean for IMSs, according to ISO 9001 for quality; ISO 14001 for environment and OHSAS 18001 for occupational health and safety (IMS–QES), that can be adapted and progressively assimilate other MSs, such as, SA 8000/ISO 26000 for social accountability, ISO 31000 for risk management and ISO/IEC 27001 for information security management, among others. The IMS–QES model was designed in the real environment of an industrial Portuguese small and medium enterprise, that over the years has been adopting, gradually, in whole or in part, individual MSSs. The developed model is based on a preliminary investigation conducted through a questionnaire. The strategy and research methods have taken into consideration the case study. Among the main findings of the survey we highlight: the creation of added value for the business through the elimination of several organisational wastes; the integrated management of the sustainability components; the elimination of conflicts between independent MS; dialogue with the main stakeholders and commitment to their ongoing satisfaction and increased contribution to the company’s competitiveness; and greater valorisation and motivation of employees as a result of the expansion of their skill base, actions and responsibilities, with their consequent empowerment. A set of key performance indicators (KPIs) constitute the support, in a perspective of business excellence, to the follow up of the organisation’s progress towards the vision and achievement of the defined objectives in the context of each component of the IMS model. The conceived model had many phases and the one presented in this work is the last required for the integration of quality, environment, safety and others individual standardised MSs. Globally, the investigation results, by themselves, justified and prioritised the conception of an IMS–QES model, to be implemented at the company where the investigation was conducted, but also a generic model of an IMS, which may be more flexible, integrator and lean as possible, potentiating the efficiency, added value both in the present and, fundamentally, for future.

Fuzzy Monte Carlo model for transmission power systems reliability based decision making

This thesis presents the Fuzzy Monte Carlo Model for Transmission Power Systems Reliability based studies (FMC-TRel) methodology, which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states. This is followed by a remedial action algorithm, based on Optimal Power Flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. For the system states that cause load curtailment, an optimization approach is applied to reduce the probability of occurrence of these states while minimizing the costs to achieve that reduction. This methodology is of most importance for supporting the transmission system operator decision making, namely in the identification of critical components and in the planning of future investments in the transmission power system. A case study based on Reliability Test System (RTS) 1996 IEEE 24 Bus is presented to illustrate with detail the application of the proposed methodology.

Scalable and efficient data processing in networked control systems

Network control systems (NCSs) are spatially distributed systems in which the communication between sensors, actuators and controllers occurs through a shared band-limited digital communication network. However, the use of a shared communication network, in contrast to using several dedicated independent connections, introduces new challenges which are even more acute in large scale and dense networked control systems. In this paper we investigate a recently introduced technique of gathering information from a dense sensor network to be used in networked control applications. Obtaining efficiently an approximate interpolation of the sensed data is exploited as offering a good tradeoff between accuracy in the measurement of the input signals and the delay to the actuation. These are important aspects to take into account for the quality of control. We introduce a variation to the state-of-the-art algorithms which we prove to perform relatively better because it takes into account the changes over time of the input signal within the process of obtaining an approximate interpolation.

A scalable and efficient approach for obtaining measurements in CAN-Based control systems

The availability of small inexpensive sensor elements enables the employment of large wired or wireless sensor networks for feeding control systems. Unfortunately, the need to transmit a large number of sensor measurements over a network negatively affects the timing parameters of the control loop. This paper presents a solution to this problem by representing sensor measurements with an approximate representation-an interpolation of sensor measurements as a function of space coordinates. A priority-based medium access control (MAC) protocol is used to select the sensor messages with high information content. Thus, the information from a large number of sensor measurements is conveyed within a few messages. This approach greatly reduces the time for obtaining a snapshot of the environment state and therefore supports the real-time requirements of feedback control loops.

Adaptive facade systems - review of performance requirements, design approaches, use cases and market needs

The paper reflects the work of COST Action TU1403 Workgroup 3/Task group 1. The aim is to identify research needs from a review of the state of the art of three aspects related to adaptive façade systems: (1) dynamic performance requirements; (2) façade design under stochastic boundary conditions and (3) experiences with adaptive façade systems and market needs.

Stochastic effects and uncertainties in assessing electromagnetic interactions with control systems

Electromagnetic compatibility, lightning, crosstalk surge voltages, Monte Carlo simulation, accident initiator

Channel estimation and ICI cancellation for adaptive OFDM systems in doubly selective channels

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2010

Moderating effects of management control systems and innovation on performance. Simple methods for correcting the effects of measurement error for interaction effects in small samples

In the accounting literature, interaction or moderating effects are usually assessed by means of OLS regression and summated rating scales are constructed to reduce measurement error bias. Structural equation models and two-stage least squares regression could be used to completely eliminate this bias, but large samples are needed. Partial Least Squares are appropriate for small samples but do not correct measurement error bias. In this article, disattenuated regression is discussed as a small sample alternative and is illustrated on data of Bisbe and Otley (in press) that examine the interaction effect of innovation and style of use of budgets on performance. Sizeable differences emerge between OLS and disattenuated regression

Studies about the atomic capabilities concept for linear control systems in physical multi-agent environments

This paper shows the impact of the atomic capabilities concept to include control-oriented knowledge of linear control systems in the decisions making structure of physical agents. These agents operate in a real environment managing physical objects (e.g. their physical bodies) in coordinated tasks. This approach is presented using an introspective reasoning approach and control theory based on the specific tasks of passing a ball and executing the offside manoeuvre between physical agents in the robotic soccer testbed. Experimental results and conclusions are presented, emphasising the advantages of our approach that improve the multi-agent performance in cooperative systems

Mean field model for spatially extended systems in the presence of multiplicative noise

We present a mean field model that describes the effect of multiplicative noise in spatially extended systems. The model can be solved analytically. For the case of the phi4 potential it predicts that the phase transition is shifted. This conclusion is supported by numerical simulations of this model in two dimensions.

Magnetic relaxation of a one-dimensional model for small particle systems with dipolar interactions: Monte Carlo simulation

Atribution as a function of the time are analyzed and this study leads to a deeper knowledge of the microscopic processes involved in the magnetic relaxation

A Feedfordward Adaptive Controller to Reduce the Imaging Time of Large-Sized Biological Samples with a SPM-Based Multiprobe Station

The time required to image large samples is an important limiting factor in SPM-based systems. In multiprobe setups, especially when working with biological samples, this drawback can make impossible to conduct certain experiments. In this work, we present a feedfordward controller based on bang-bang and adaptive controls. The controls are based in the difference between the maximum speeds that can be used for imaging depending on the flatness of the sample zone. Topographic images of Escherichia coli bacteria samples were acquired using the implemented controllers. Results show that to go faster in the flat zones, rather than using a constant scanning speed for the whole image, speeds up the imaging process of large samples by up to a 4x factor.

The Detector Control Systems for the CMS Resistive Plate Chamber at LHC

The RPC Detector Control System (RCS) is the main subject of this PhD work. The project, involving the Lappeenranta University of Technology, the Warsaw University and INFN of Naples, is aimed to integrate the different subsystems for the RPC detector and its trigger chain in order to develop a common framework to control and monitoring the different parts. In this project, I have been strongly involved during the last three years on the hardware and software development, construction and commissioning as main responsible and coordinator. The CMS Resistive Plate Chambers (RPC) system consists of 912 double-gap chambers at its start-up in middle of 2008. A continuous control and monitoring of the detector, the trigger and all the ancillary sub-systems (high voltages, low voltages, environmental, gas, and cooling), is required to achieve the operational stability and reliability of a so large and complex detector and trigger system. Role of the RPC Detector Control System is to monitor the detector conditions and performance, control and monitor all subsystems related to RPC and their electronics and store all the information in a dedicated database, called Condition DB. Therefore the RPC DCS system has to assure the safe and correct operation of the sub-detectors during all CMS life time (more than 10 year), detect abnormal and harmful situations and take protective and automatic actions to minimize consequential damages. The analysis of the requirements and project challenges, the architecture design and its development as well as the calibration and commissioning phases represent themain tasks of the work developed for this PhD thesis. Different technologies, middleware and solutions has been studied and adopted in the design and development of the different components and a big challenging consisted in the integration of these different parts each other and in the general CMS control system and data acquisition framework. Therefore, the RCS installation and commissioning phase as well as its performance and the first results, obtained during the last three years CMS cosmic runs, will be

Selectivity of chemical weed control systems in conventional cotton

Cotton is highly susceptible to the interference imposed by weed community, being therefore essential to adopt control measures ensuring the crop yield. Herbicides are the primary method of weed control in large-scale areas of production, and usually more than one herbicide application is necessary due to the extensive crop cycle. This study aimed to evaluate the selectivity of different chemical weed control systems for conventional cotton. The experiment took place in the field in a randomized block design, with twenty nine treatments and four replications in a split plot layout (adjacent double check). Results showed that triple mixtures in pre-emergence increased the chance of observing reductions in the cotton yield. To avoid reductions in crop yield, users should proceed to a maximum mixture of two herbicides in pre-emergence, followed by S-metolachlor over the top, followed by one post-emergence mixture application of pyrithiobac-sodium + trifloxysulfuron-sodium.