842 resultados para performance-based engineering
Resumo:
The main aim of this research is to demonstrate strategic supplier performance evaluation of a UK-based manufacturing organisation using an integrated analytical framework. Developing long term relationship with strategic suppliers is common in today's industry. However, monitoring suppliers' performance all through the contractual period is important in order to ensure overall supply chain performance. Therefore, client organisations need to measure suppliers' performance dynamically and inform them on improvement measures. Although there are many studies introducing innovative supplier performance evaluation frameworks and empirical researches on identifying criteria for supplier evaluation, little has been reported on detailed application of strategic supplier performance evaluation and its implication on overall performance of organisation. Additionally, majority of the prior studies emphasise on lagging factors (quality, delivery schedule and value/cost) for supplier selection and evaluation. This research proposes both leading (organisational practices, risk management, environmental and social practices) and lagging factors for supplier evaluation and demonstrates a systematic method for identifying those factors with the involvement of relevant stakeholders and process mapping. The contribution of this article is a real-life case-based action research utilising an integrated analytical model that combines quality function deployment and the analytic hierarchy process method for suppliers' performance evaluation. The effectiveness of the method has been demonstrated through number of validations (e.g. focus group, business results, and statistical analysis). Additionally, the study reveals that enhanced supplier performance results positive impact on operational and business performance of client organisation.
Resumo:
A hybrid passive-active damping solution with improved system stability margin and enhanced dynamic performance is proposed for high power grid interactive converters. In grid connected active rectifier/inverter application, line side LCL filter improves the high frequency attenuation and makes the converter compatible with the stringent grid power quality regulations. Passive damping though offers a simple and reliable solution but it reduces overall converter efficiency. Active damping solutions do not increase the system losses but can guarantee the stable operation up to a certain speed of dynamic response which is limited by the maximum bandwidth of the current controller. This paper examines this limit and introduces a concept of hybrid passive-active damping solution with improved stability margin and high dynamic performance for line side LCL filter based active rectifier/inverter applications. A detailed design, analysis of the hybrid approach and trade-off between system losses and dynamic performance in grid connected applications are reported. Simulation and experimental results from a 10 kVA prototype demonstrate the effectiveness of the proposed solution. An analytical study on system stability and dynamic response with the variations of various controller and passive filter parameters is presented.
Resumo:
In the contemporary business environment, to adhere to the need of the customers, caused the shift from mass production to mass-customization. This necessitates the supply chain (SC) to be effective flexible. The purpose of this paper is to seek flexibility through adoption of family-based dispatching rules under the influence of inventory system implemented at downstream echelons of an industrial supply chain network. We compared the family-based dispatching rules in existing literature under the purview of inventory system and information sharing within a supply chain network. The dispatching rules are compared for Average Flow Time performance, which is averaged over the three product families. The performance is measured using extensive discrete event simulation process. Given the various inventory related operational factors at downstream echelons, the present paper highlights the importance of strategically adopting appropriate family-based dispatching rule at the manufacturing end. In the environment of mass customization, it becomes imperative to adopt the family-based dispatching rule from the system wide SC perspective. This warrants the application of intra as well as inter-echelon information coordination. The holonic paradigm emerges in this research stream, amidst the holistic approach and the vital systemic approach. The present research shows its novelty in triplet. Firstly, it provides leverage to manager to strategically adopting a dispatching rule from the inventory system perspective. Secondly, the findings provide direction for the attenuation of adverse impact accruing from demand amplification (bullwhip effect) in the form of inventory levels by appropriately adopting family-based dispatching rule. Thirdly, the information environment is conceptualized under the paradigm of Koestler's holonic theory.
Resumo:
Liquid-level sensing technologies have attracted great prominence, because such measurements are essential to industrial applications, such as fuel storage, flood warning and in the biochemical industry. Traditional liquid level sensors are based on electromechanical techniques; however they suffer from intrinsic safety concerns in explosive environments. In recent years, given that optical fiber sensors have lots of well-established advantages such as high accuracy, costeffectiveness, compact size, and ease of multiplexing, several optical fiber liquid level sensors have been investigated which are based on different operating principles such as side-polishing the cladding and a portion of core, using a spiral side-emitting optical fiber or using silica fiber gratings. The present work proposes a novel and highly sensitive liquid level sensor making use of polymer optical fiber Bragg gratings (POFBGs). The key elements of the system are a set of POFBGs embedded in silicone rubber diaphragms. This is a new development building on the idea of determining liquid level by measuring the pressure at the bottom of a liquid container, however it has a number of critical advantages. The system features several FBG-based pressure sensors as described above placed at different depths. Any sensor above the surface of the liquid will read the same ambient pressure. Sensors below the surface of the liquid will read pressures that increase linearly with depth. The position of the liquid surface can therefore be approximately identified as lying between the first sensor to read an above-ambient pressure and the next higher sensor. This level of precision would not in general be sufficient for most liquid level monitoring applications; however a much more precise determination of liquid level can be made by linear regression to the pressure readings from the sub-surface sensors. There are numerous advantages to this multi-sensor approach. First, the use of linear regression using multiple sensors is inherently more accurate than using a single pressure reading to estimate depth. Second, common mode temperature induced wavelength shifts in the individual sensors are automatically compensated. Thirdly, temperature induced changes in the sensor pressure sensitivity are also compensated. Fourthly, the approach provides the possibility to detect and compensate for malfunctioning sensors. Finally, the system is immune to changes in the density of the monitored fluid and even to changes in the effective force of gravity, as might be obtained in an aerospace application. The performance of an individual sensor was characterized and displays a sensitivity (54 pm/cm), enhanced by more than a factor of 2 when compared to a sensor head configuration based on a silica FBG published in the literature, resulting from the much lower elastic modulus of POF. Furthermore, the temperature/humidity behavior and measurement resolution were also studied in detail. The proposed configuration also displays a highly linear response, high resolution and good repeatability. The results suggest the new configuration can be a useful tool in many different applications, such as aircraft fuel monitoring, and biochemical and environmental sensing, where accuracy and stability are fundamental. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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We present, for the first time, a detailed investigation of the impact of second order co-propagating Raman pumping on long-haul 100G WDM DP-QPSK coherent transmission of up to 7082 km using Raman fibre laser based configurations. Signal power and noise distributions along the fibre for each pumping scheme were characterised both numerically and experimentally. Based on these pumping schemes, the Q factor penalties versus co-pump power ratios were experimentally measured and quantified. A significant Q factor penalty of up to 4.15 dB was observed after 1666 km using symmetric bidirectional pumping, compared with counter-pumping only. Our results show that whilst using co-pumping minimises the intra-cavity signal power variation and amplification noise, the Q factor penalty with co-pumping was too great for any advantage to be seen. The relative intensity noise (RIN) characteristics of the induced fibre laser and the output signal, and the intra-cavity RF spectra of the fibre laser are also presented. We attribute the Q factor degradation to RIN induced penalty due to RIN being transferred from the first order fibre laser and second order co-pump to the signal. More importantly, there were two different fibre lasing regimes contributing to the amplification. It was random distributed feedback lasing when using counter-pumping only and conventional Fabry-Perot cavity lasing when using all bidirectional pumping schemes. This also results in significantly different performances due to different laser cavity lengths for these two classes of laser.
Resumo:
This study explores the ongoing pedagogical development of a number of undergraduate design and engineering programmes in the United Kingdom. Observations and data have been collected over several cohorts to bring a valuable perspective to the approaches piloted across two similar university departments while trialling a number of innovative learning strategies. In addition to the concurrent institutional studies the work explores curriculum design that applies the principles of Co-Design, multidisciplinary and trans disciplinary learning, with both engineering and product design students working alongside each other through a practical problem solving learning approach known as the CDIO learning initiative (Conceive, Design Implement and Operate) [1]. The study builds on previous work presented at the 2010 EPDE conference: The Effect of Personality on the Design Team: Lessons from Industry for Design Education [2]. The subsequent work presented in this paper applies the findings to mixed design and engineering team based learning, building on the insight gained through a number of industrial process case studies carried out in current design practice. Developments in delivery also aligning the CDIO principles of learning through doing into a practice based, collaborative learning experience and include elements of the TRIZ creative problem solving technique [3]. The paper will outline case studies involving a number of mixed engineering and design student projects that highlight the CDIO principles, combined with an external industrial design brief. It will compare and contrast the learning experience with that of a KTP derived student project, to examine an industry based model for student projects. In addition key areas of best practice will be presented, and student work from each mode will be discussed at the conference.
Resumo:
Student engagement is vital in enhancing the student experience and encouraging deeper learning. Involving students in the design of assessment criteria is one way in which to increase student engagement. In 2011, a marking matrix was used at Aston University (UK) for logbook assessment (Group One) in a project-based learning module. The next cohort of students in 2012 (Group Two) were asked to collaboratively redesign the matrix and were given a questionnaire about the exercise. Group Two initially scored a lower average logbook mark than Group One. However, Group Two showed the greatest improvement between assessments, and the quality of, and commitment to, logbooks was noticeably improved. Student input resulted in a more defined, tougher mark scheme. However, this provided an improved feedback system that gave more scope for self-improvement. The majority of students found the exercise incorporated their ideas, enhanced their understanding, and was useful in itself.
Resumo:
A high performance liquid-level sensor based on microstructured polymer optical fiber Bragg grating (mPOFBG) array sensors is reported in detail. The sensor sensitivity is found to be 98pm/cm of liquid, enhanced by more than a factor of 9 compared to a reported silica fiber-based sensor.
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We demonstrate that a distributed Raman amplification scheme based on random distributed feedback (DFB) fiber laser enables bidirectional second-order Raman pumping without increasing relative intensity noise (RIN) of the signal. This extends the reach of 10 × 116 Gb/s DP-QPSK WDM transmission up to 7915 km, compared with conventional Raman amplification schemes. Moreover, this scheme gives the longest maximum transmission distance among all the Raman amplification schemes presented in this paper, whilst maintaining relatively uniform and symmetric signal power distribution, and is also adjustable in order to be highly compatible with different nonlinearity compensation techniques, including mid-link optical phase conjugation (OPC) and nonlinear Fourier transform (NFT).
Resumo:
The stress sensitivity of polymer optical fibre (POF) based Fabry-Perot sensors formed by two uniform Bragg gratings with finite dimensions is investigated. POF has received high interest in recent years due to its different material properties compared to its silica counterpart. Biocompatibility, a higher failure strain and the highly elastic nature of POF are some of the main advantages. The much lower Young’s modulus of polymer materials compared to silica offers enhanced stress sensitivity to POF based sensors which renders them great candidates for acoustic wave receivers and any kind of force detection. The main drawback in POF technology is perhaps the high fibre loss. In a lossless fibre the sensitivity of an interferometer is proportional to its cavity length. However, the presence of the attenuation along the optical path can significantly reduce the finesse of the Fabry-Perot interferometer and it can negatively affect its sensitivity at some point. The reflectivity of the two gratings used to form the interferometer can be also reduced as the fibre loss increases. In this work, a numerical model is developed to study the performance of POF based Fabry-Perot sensors formed by two uniform Bragg gratings with finite dimensions. Various optical and physical properties are considered such as grating physical length, grating effective length which indicates the point where the light is effectively reflected, refractive index modulation of the grating, cavity length of the interferometer, attenuation and operating wavelength. Using this model, we are able to identify the regimes in which the PMMA based sensor offer enhanced stress sensitivity compared to silica based one.
Resumo:
Markovian models are widely used to analyse quality-of-service properties of both system designs and deployed systems. Thanks to the emergence of probabilistic model checkers, this analysis can be performed with high accuracy. However, its usefulness is heavily dependent on how well the model captures the actual behaviour of the analysed system. Our work addresses this problem for a class of Markovian models termed discrete-time Markov chains (DTMCs). We propose a new Bayesian technique for learning the state transition probabilities of DTMCs based on observations of the modelled system. Unlike existing approaches, our technique weighs observations based on their age, to account for the fact that older observations are less relevant than more recent ones. A case study from the area of bioinformatics workflows demonstrates the effectiveness of the technique in scenarios where the model parameters change over time.
Resumo:
The automotive industry combines a multitude of professionals to develop a modern car successfully. Within the design and development teams the collaboration and interface between Engineers and Designers is critical to ensure design intent is communicated and maintained throughout the development process. This study highlights recent industry practice with the emergence of Concept Engineers in design teams at Jaguar Land Rover Automotive group. The role of the Concept Engineer emphasises the importance of the Engineering and Design/Styling interface with the Concept engineer able to interact and understand the challenges and specific languages of each specialist area, hence improving efficiency and communication within the design team. Automotive education tends to approach design from two distinct directions, that of engineering design through BSc courses or a more styling design approach through BA and BDes routes. The educational challenge for both types of course is to develop engineers and stylist's who have greater understanding and experience of each other's specialist perspective of design and development. The study gives examples of two such courses in the UK who are developing programmes to help students widen their understanding of the engineering and design spectrum. Initial results suggest the practical approach has been well received by students and encouraged by industry as they seek graduates with specialist knowledge but also a wider appreciation of their role within the design process.
Resumo:
Parameter design is an experimental design and analysis methodology for developing robust processes and products. Robustness implies insensitivity to noise disturbances. Subtle experimental realities, such as the joint effect of process knowledge and analysis methodology, may affect the effectiveness of parameter design in precision engineering; where the objective is to detect minute variation in product and process performance. In this thesis, approaches to statistical forced-noise design and analysis methodologies were investigated with respect to detecting performance variations. Given a low degree of process knowledge, Taguchi's methodology of signal-to-noise ratio analysis was found to be more suitable in detecting minute performance variations than the classical approach based on polynomial decomposition. Comparison of inner-array noise (IAN) and outer-array noise (OAN) structuring approaches showed that OAN is a more efficient design for precision engineering. ^
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Pavement performance is one of the most important components of the pavement management system. Prediction of the future performance of a pavement section is important in programming maintenance and rehabilitation needs. Models for predicting pavement performance have been developed on the basis of traffic and age. The purpose of this research is to extend the use of a relatively new approach to performance prediction in pavement performance modeling using adaptive logic networks (ALN). Adaptive logic networks have recently emerged as an effective alternative to artificial neural networks for machine learning tasks. ^ The ALN predictive methodology is applicable to a wide variety of contexts including prediction of roughness based indices, composite rating indices and/or individual pavement distresses. The ALN program requires key information about a pavement section, including the current distress indexes, pavement age, climate region, traffic and other variables to predict yearly performance values into the future. ^ This research investigates the effect of different learning rates of the ALN in pavement performance modeling. It can be used at both the network and project level for predicting the long term performance of a road network. Results indicate that the ALN approach is well suited for pavement performance prediction modeling and shows a significant improvement over the results obtained from other artificial intelligence approaches. ^