Factors affecting human reliability in the chemical process industry

This research was concerned with identifying factors which may influence human reliability within chemical process plants - these factors are referred to as Performance Shaping Factors (PSFs). Following a period of familiarization within the industry, a number of case studies were undertaken covering a range of basic influencing factors. Plant records and site `lost time incident reports' were also used as supporting evidence for identifying and classifying PSFs. In parallel to the investigative research, the available literature appertaining to human reliability assessment and PSFs was considered in relation to the chemical process plan environment. As a direct result of this work, a PSF classification structure has been produced with an accompanying detailed listing. Phase two of the research considered the identification of important individual PSFs for specific situations. Based on the experience and data gained during phase one, it emerged that certain generic features of a task influenced PSF relevance. This led to the establishment of a finite set of generic task groups and response types. Similarly, certain PSFs influence some human errors more than others. The result was a set of error type key words, plus the identification and classification of error causes with their underlying error mechanisms. By linking all these aspects together, a comprehensive methodology has been forwarded as the basis of a computerized aid for system designers. To recapitulate, the major results of this research have been: One, the development of a comprehensive PSF listing specifically for the chemical process industries with a classification structure that facilitates future updates; and two, a model of identifying relevant SPFs and their order of priority. Future requirements are the evaluation of the PSF listing and the identification method. The latter must be considered both in terms of `useability' and its success as a design enhancer, in terms of an observable reduction in important human errors.

Management information:design of a system for change identification

This thesis deals with the problem of Information Systems design for Corporate Management. It shows that the results of applying current approaches to Management Information Systems and Corporate Modelling fully justify a fresh look to the problem. The thesis develops an approach to design based on Cybernetic principles and theories. It looks at Management as an informational process and discusses the relevance of regulation theory to its practice. The work proceeds around the concept of change and its effects on the organization's stability and survival. The idea of looking at organizations as viable systems is discussed and a design to enhance survival capacity is developed. It takes Ashby's theory of adaptation and developments on ultra-stability as a theoretical framework and considering conditions for learning and foresight deduces that a design should include three basic components: A dynamic model of the organization- environment relationships; a method to spot significant changes in the value of the essential variables and in a certain set of parameters; and a Controller able to conceive and change the other two elements and to make choices among alternative policies. Further considerations of the conditions for rapid adaptation in organisms composed of many parts, and the law of Requisite Variety determine that successful adaptive behaviour requires certain functional organization. Beer's model of viable organizations is put in relation to Ashby's theory of adaptation and regulation. The use of the Ultra-stable system as abstract unit of analysis permits developing a rigorous taxonomy of change; it starts distinguishing between change with in behaviour and change of behaviour to complete the classification with organizational change. It relates these changes to the logical categories of learning connecting the topic of Information System design with that of organizational learning.

The process of strategic change:a management perspective

This thesis is concerned with the management processes concerned with complex strategic decision in organisations. The research has sought to explore these processes by taking as its focus the reconstruction of decision processes a) on the basis of an historical study of an industry and in particular a major company in that industry; and b) the perception and understanding of strategic decision processes and change by managers involved in companies in that industry. The main body of analysis and theoretical contributions arise from the detailed analysis of extended depth interviews with managers carried out in 1980 and 1983 which trace thirteen years of the strategic development of a firm. In so doing, extensive use is made of verbatim accounts by managers of events and their interpretation of events. This is then compared with data gathered from.similar interviews with managers of two other companies and examined in the light of existing research and theory in the field. The thesis both provides a detailed insight into the processes associated with the identification and resolution of complex strategic issues and also generates a body of theory concerning the mechanisms by which strategic decisions and the processes of strategic change are interwoven with the cultural and political fabric of organisations. The thesis is divided into four parts. The first part deals with the background to the research, provid1ng a fuller summary of the purpose, structure and content of the thesis and a discussion of relevant previous research and the methodology employed herein. The second part mainly provides case studies of the industry and the main company studied. The third part is a detailed presentation and analysis of data. The fourth part is a synthesis of the findings and consolidation of the theoretical interpretation advanced in the thesis.

Pre-entry organisational identification:considering the theoretical and managerial implications of future members’ identification with an organisation

From a Social Identity Theory perspective, organisational identification arises through a cognitive process of self-categorisation. As a consequence a person need not have a formal relationship with an organisation in order to identify with it. In this conceptual paper, the authors draw on this proposal to argue that future members are capable of identifying with an organisation prior to entry, and that this initial pre-entry identification could contribute to a person’s subsequent post-entry organisational identification. The paper further suggests that because no distinction need be drawn between organisational identification in current and future members, we might expect to find the same antecedents of identification in both instances. The group engagement model (Tyler and Blader 2003) is called on to propose that when a future member experiences pride in, and respect from, an organisation before they join, this should positively influence their pre-entry organisational identification. The authors explore the managerial implications of these propositions, and argue that an organisation’s actions and practices that have been shown to influence a post-entry organisational identification should have an equivalent impact on future members’ organisational identification when observed during the pre-entry period. Two examples of such practices, organisational support and organisational communication, are used to illustrate this suggestion and a number of ways are discussed through which these practices may be experienced by a person before they join an organisation.

An agent approach to improving radio frequency identification enabled Returnable Transport Equipment

Returnable transport equipment (RTE) such as pallets form an integral part of the supply chain and poor management leads to costly losses. Companies often address this matter by outsourcing the management of RTE to logistics service providers (LSPs). LSPs are faced with the task to provide logistical expertise to reduce RTE related waste, whilst differentiating their own services to remain competitive. In the current challenging economic climate, the role of the LSP to deliver innovative ways to achieve competitive advantage has never been so important. It is reported that radio frequency identification (RFID) application to RTE enables LSPs such as DHL to gain competitive advantage and offer clients improvements such as loss reduction, process efficiency improvement and effective security. However, the increased visibility and functionality of RFID enabled RTE requires further investigation in regards to decision‐making. The distributed nature of the RTE network favours a decentralised decision‐making format. Agents are an effective way to represent objects from the bottom‐up, capturing the behaviour and enabling localised decision‐making. Therefore, an agent based system is proposed to represent the RTE network and utilise the visibility and data gathered from RFID tags. Two types of agents are developed in order to represent the trucks and RTE, which have bespoke rules and algorithms in order to facilitate negotiations. The aim is to create schedules, which integrate RTE pick‐ups as the trucks go back to the depot. The findings assert that: - agent based modelling provides an autonomous tool, which is effective in modelling RFID enabled RTE in a decentralised utilising the real‐time data facility. ‐ the RFID enabled RTE model developed enables autonomous agent interaction, which leads to a feasible schedule integrating both forward and reverse flows for each RTE batch. ‐ the RTE agent scheduling algorithm developed promotes the utilisation of RTE by including an automatic return flow for each batch of RTE, whilst considering the fleet costs andutilisation rates. ‐ the research conducted contributes an agent based platform, which LSPs can use in order to assess the most appropriate strategies to implement for RTE network improvement for each of their clients.

Event trigger identification for biomedical events extraction using domain knowledge

Motivation: In molecular biology, molecular events describe observable alterations of biomolecules, such as binding of proteins or RNA production. These events might be responsible for drug reactions or development of certain diseases. As such, biomedical event extraction, the process of automatically detecting description of molecular interactions in research articles, attracted substantial research interest recently. Event trigger identification, detecting the words describing the event types, is a crucial and prerequisite step in the pipeline process of biomedical event extraction. Taking the event types as classes, event trigger identification can be viewed as a classification task. For each word in a sentence, a trained classifier predicts whether the word corresponds to an event type and which event type based on the context features. Therefore, a well-designed feature set with a good level of discrimination and generalization is crucial for the performance of event trigger identification. Results: In this article, we propose a novel framework for event trigger identification. In particular, we learn biomedical domain knowledge from a large text corpus built from Medline and embed it into word features using neural language modeling. The embedded features are then combined with the syntactic and semantic context features using the multiple kernel learning method. The combined feature set is used for training the event trigger classifier. Experimental results on the golden standard corpus show that >2.5% improvement on F-score is achieved by the proposed framework when compared with the state-of-the-art approach, demonstrating the effectiveness of the proposed framework. © 2014 The Author 2014. The source code for the proposed framework is freely available and can be downloaded at http://cse.seu.edu.cn/people/zhoudeyu/ETI_Sourcecode.zip.

Methods of Color Images Procession for Further Identification of the Object

The offered paper deals with the problems of color images preliminary procession. Among these are: interference control (local ones and noise) and extraction of the object from the background on the stage preceding the process of contours extraction. It was considered for a long time that execution of smoothing in segmentation through the boundary extraction is inadmissible, but the described methods and the obtained results evidence about expedience of using the noise control methods.

Parameter Identification of a Fed-Batch Cultivation of S. Cerevisiae using Genetic Algorithms

Fermentation processes as objects of modelling and high-quality control are characterized with interdependence and time-varying of process variables that lead to non-linear models with a very complex structure. This is why the conventional optimization methods cannot lead to a satisfied solution. As an alternative, genetic algorithms, like the stochastic global optimization method, can be applied to overcome these limitations. The application of genetic algorithms is a precondition for robustness and reaching of a global minimum that makes them eligible and more workable for parameter identification of fermentation models. Different types of genetic algorithms, namely simple, modified and multi-population ones, have been applied and compared for estimation of nonlinear dynamic model parameters of fed-batch cultivation of S. cerevisiae.

A Conceptual Foresight Model to Investigate the Adoption of Radio Frequency Identification Technology in the English National Health Service

Radio Frequency Identification Technology (RFID) adoption in healthcare settings has the potential to reduce errors, improve patient safety, streamline operational processes and enable the sharing of information throughout supply chains. RFID adoption in the English NHS is limited to isolated pilot studies. Firstly, this study investigates the drivers and inhibitors to RFID adoption in the English NHS from the perspective of the GS1 Healthcare User Group (HUG) tasked with coordinating adoption across private and public sectors. Secondly a conceptual model has been developed and deployed, combining two of foresight’s most popular methods; scenario planning and technology roadmapping. The model addresses the weaknesses of each foresight technique as well as capitalizing on their individual, inherent strengths. Semi structured interviews, scenario planning workshops and a technology roadmapping exercise were conducted with the members of the HUG over an 18-month period. An action research mode of enquiry was utilized with a thematic analysis approach for the identification and discussion of the drivers and inhibitors of RFID adoption. The results of the conceptual model are analysed in comparison to other similar models. There are implications for managers responsible for RFID adoption in both the NHS and its commercial partners, and for foresight practitioners. Managers can leverage the insights gained from identifying the drivers and inhibitors to RFID adoption by making efforts to influence the removal of inhibitors and supporting the continuation of the drivers. The academic contribution of this aspect of the thesis is in the field of RFID adoption in healthcare settings. Drivers and inhibitors to RFID adoption in the English NHS are compared to those found in other settings. The implication for technology foresight practitioners is a proof of concept of a model combining scenario planning and technology roadmapping using a novel process. The academic contribution to the field of technology foresight is the conceptual development of foresight model that combines two popular techniques and then a deployment of the conceptual foresight model in a healthcare setting exploring the future of RFID technology.

Understanding and improving the manufacturing and changeover process in Saudi Arabian business - a multiple case study approach

The importance of the changeover process in the manufacturing industry is becoming widely recognised. Changeover is a complete process of changing between the manufacture of one product to manufacture of an alternative product until specified production and quality rates are reached. The initiatives to improve changeover exist in industry, as better changeover process typically contribute to improved quality performance. A high-quality and reliable changeover process can be achieved through implementation of continuous or radical improvements. This research examines the changeover process of Saudi Arabian manufacturing firms because Saudi Arabia’s government is focused on the expansion of GDP and increasing the number of export manufacturing firms. Furthermore, it is encouraging foreign manufacturing firms to invest within Saudi Arabia. These initiatives, therefore, require that Saudi manufacturing businesses develop the changeover practice in order to compete in the market and achieve the government’s objectives. Therefore, the aim of this research is to discover the current status of changeover process implementation in Saudi Arabian manufacturing businesses. To achieve this aim, the main objective of this research is to develop a conceptual model to understand and examine the effectiveness of the changeover process within Saudi Arabian manufacturing firms, facilitating identification of those activities that affect the reliability and high-quality of the process. In order to provide a comprehensive understanding of this area, this research first explores the concept of quality management and its relationship to firm performance and the performance of manufacturing changeover. An extensive body of literature was reviewed on the subject of lean manufacturing and changeover practice. A research conceptual model was identified based on this review, and focus was on providing high-quality and reliable manufacturing changeover processes during set-up in a dynamic environment. Exploratory research was conducted in sample Saudi manufacturing firms to understand the features of the changeover process within the manufacturing sector, and as a basis for modifying the proposed conceptual model. Qualitative research was employed in the study with semi-structured interviews, direct observations and documentation in order to understand the real situation such as actual daily practice and current status of changeover process in the field. The research instrument, the Changeover Effectiveness Assessment Tool (CEAT) was developed to evaluate changeover practices. A pilot study was conducted by examining the CEAT, proposed for the main research. Consequently, the conceptual model was modified and CEAT was improved in response to the pilot study findings. Case studies have been conducted within eight Saudi manufacturing businesses. These case studies assessed the implementation of manufacturing changeover practice in the lighting and medical products sectors. These two sectors were selected based on their operation strategy which was batch production as well as the fact that they fulfilled the research sampling strategy. The outcomes of the research improved the conceptual model, ultimately to facilitate the firms’ adoption and rapid implementation of a high-quality and reliability changeover during the set-up process. The main finding of this research is that Quality’s factors were considering the lowest levels comparing to the other factors which are People, Process and Infrastructure. This research contributes to enable Saudi businesses to implement the changeover process by adopting the conceptual model. In addition, the guidelines for facilitating implementation were provided in this thesis. Therefore, this research provides insight to enable the Saudi manufacturing industry to be more responsive to rapidly changing customer demands.

Identification and characterization of interfering products in fire debris analysis

The purpose of this research was to study interfering products in fire debris analysis, including their identification and characterization. Different substrates were classified, burned, extracted and analyzed in order to identify all the interfering products that they may release. It has been shown that these products come from three different sources: substrate background products, pyrolysis products and possibly combustion products. Different parameters in the creation of these products were evaluated such as the extinguishment process as well as the weathering of the sample prior to the analysis. It has been shown that the presence of these products is not always constant and thus, makes it difficult to extrapolate data to similar cases. Furthermore, some of these products are similar to the ones found in ignitable liquids. Finally, it shows one more time how important it is to collect and analyze control samples in fire debris analysis. ^

Presumptive Identification of the Fungal Communities in Cystic Fibrosis Patients' Sputum Using Amplicon Length Heterogeneity Polymerase Chain Reaction

This thesis would not have been possible without the aid of my family, friends, laboratory members, and professors. First and foremost, I would like to thank Dr. Kalai Mathee for allowing me to enter her lab in August 2007 and enabling to embark on this journey. This experience has transformed me into more mature scientist, teaching me how to ask the right questions and the process needed to solve them. I would also like to acknowledge Dr. Lisa Schneper. She has helped me throughout the whole process, by graciously giving me input at every step of the way. I would like to express gratitude to Dr. Jennifer Richards for all her input in writing the thesis. She has been a great teacher and being in her class has been a pleasure. Moreover, I would like to thank all the committee members for their constructive criticism throughout the process. When I entered the lab in August, there was one person who literally was by my side, Melissa Doud. Without your input and guidance I would not have even been able to do these experiments. I would also like to thank you and Dr. Light for allowing me to meet some cystic fibrosis patients. It has allowed me to put a face on the disease, and help the patients' fight. For a period before I had entered the lab, Ms. Doud had an apprentice, who started the fungal aspect of the project, Caroline Veronese. Her initial work has enabled me to prefect the protocols and complete the ITS 1 region.One very unique aspect about Dr. Mathee's lab is the camaraderie. I would like to thank all the lab members for the good times in and out of the lab. These individuals have been able to make smile and laugh in parties and lab meetings. I would like to individually thank Balachandar Dananjeyan, Deepak Balasubramanian, and V arinderpal Singh Pannu for all the PCR help and Natalie Maricic for the laughs and being a great classmate. Last, but not least, I would like to acknowledge my family and friends for their support and keeping me sane: Cecilia, my mother, Mohammad, my father, Amir, my older brother, Billal, my younger brother, Ouday Akkari and Stephanie De Bedout, my best friends.

Impact of high pCO2 and warmer temperatures on the process of silica biomineralization in the sponge Mycale grandis

Siliceous sponges have survived pre-historical mass extinction events caused by ocean acidification and recent studies suggest that siliceous sponges will continue to resist predicted increases in ocean acidity. In this study, we monitored silica biomineralization in the Hawaiian sponge Mycale grandis under predicted pCO2 and sea surface temperature scenarios for 2100. Our goal was to determine if spicule biomineralization was enhanced or repressed by ocean acidification and thermal stress by monitoring silica uptake rates during short-term (48 h) experiments and comparing biomineralized tissue ratios before and after a long-term (26 d) experiment. In the short-term experiment, we found that silica uptake rates were not impacted by high pCO2 (1050 µatm), warmer temperatures (27°C), or combined high pCO2 with warmer temperature (1119 µatm; 27°C) treatments. The long-term exposure experiments revealed no effect on survival or growth rates of M. grandis to high pCO2 (1198 µatm), warmer temperatures (25.6°C), or combined high pCO2 with warmer temperature (1225 µatm, 25.7°C) treatments, indicating that M. grandis will continue to prosper under predicted increases in pCO2 and sea surface temperature. However, ash-free dry weight to dry weight ratios, subtylostyle lengths, and silicified weight to dry weight ratios decreased under conditions of high pCO2 and combined pCO2 warmer temperature treatments. Our results show that rising ocean acidity and temperature have marginal negative effects on spicule biomineralization and will not affect sponge survival rates of M. grandis.

A constraint and position identification (CPI) approach for the synthesis of decoupled spatial translational compliant parallel manipulators

This paper introduces a screw theory based method termed constraint and position identification (CPI) approach to synthesize decoupled spatial translational compliant parallel manipulators (XYZ CPMs) with consideration of actuation isolation. The proposed approach is based on a systematic arrangement of rigid stages and compliant modules in a three-legged XYZ CPM system using the constraint spaces and the position spaces of the compliant modules. The constraint spaces and the position spaces are firstly derived based on the screw theory instead of using the rigid-body mechanism design experience. Additionally, the constraint spaces are classified into different constraint combinations, with typical position spaces depicted via geometric entities. Furthermore, the systematic synthesis process based on the constraint combinations and the geometric entities is demonstrated via several examples. Finally, several novel decoupled XYZ CPMs with monolithic configurations are created and verified by finite elements analysis. The present CPI approach enables experts and beginners to synthesize a variety of decoupled XYZ CPMs with consideration of actuation isolation by selecting an appropriate constraint and an optimal position for each of the compliant modules according to a specific application.

A Molecular-scale Programmable Stochastic Process Based On Resonance Energy Transfer Networks: Modeling And Applications

While molecular and cellular processes are often modeled as stochastic processes, such as Brownian motion, chemical reaction networks and gene regulatory networks, there are few attempts to program a molecular-scale process to physically implement stochastic processes. DNA has been used as a substrate for programming molecular interactions, but its applications are restricted to deterministic functions and unfavorable properties such as slow processing, thermal annealing, aqueous solvents and difficult readout limit them to proof-of-concept purposes. To date, whether there exists a molecular process that can be programmed to implement stochastic processes for practical applications remains unknown.

In this dissertation, a fully specified Resonance Energy Transfer (RET) network between chromophores is accurately fabricated via DNA self-assembly, and the exciton dynamics in the RET network physically implement a stochastic process, specifically a continuous-time Markov chain (CTMC), which has a direct mapping to the physical geometry of the chromophore network. Excited by a light source, a RET network generates random samples in the temporal domain in the form of fluorescence photons which can be detected by a photon detector. The intrinsic sampling distribution of a RET network is derived as a phase-type distribution configured by its CTMC model. The conclusion is that the exciton dynamics in a RET network implement a general and important class of stochastic processes that can be directly and accurately programmed and used for practical applications of photonics and optoelectronics. Different approaches to using RET networks exist with vast potential applications. As an entropy source that can directly generate samples from virtually arbitrary distributions, RET networks can benefit applications that rely on generating random samples such as 1) fluorescent taggants and 2) stochastic computing.

By using RET networks between chromophores to implement fluorescent taggants with temporally coded signatures, the taggant design is not constrained by resolvable dyes and has a significantly larger coding capacity than spectrally or lifetime coded fluorescent taggants. Meanwhile, the taggant detection process becomes highly efficient, and the Maximum Likelihood Estimation (MLE) based taggant identification guarantees high accuracy even with only a few hundred detected photons.

Meanwhile, RET-based sampling units (RSU) can be constructed to accelerate probabilistic algorithms for wide applications in machine learning and data analytics. Because probabilistic algorithms often rely on iteratively sampling from parameterized distributions, they can be inefficient in practice on the deterministic hardware traditional computers use, especially for high-dimensional and complex problems. As an efficient universal sampling unit, the proposed RSU can be integrated into a processor / GPU as specialized functional units or organized as a discrete accelerator to bring substantial speedups and power savings.