Programming Integrated Surgical Operations and Preventive Maintenance Activities

Part 2: Knowledge-Based ServicesInternational audienceThe operating theatre (OT) represents a significant component of the technical means centre. This facility is the largest cost and revenue centre. To be efficient, it needs an optimal operational pro- gramme, which takes into account maintenance activi- ties and not only surgical operations. To build such a programme, various methods have been used: mixed integer programming (MIP), three classic heuristics for Bin-Packing and a coupling of the first alterna- tive with a stochastic descent (SD). Then we compare the obtained results from generated data

Solving for an Optimal Batch Size for a Single Machine Using the Closed-form Equations to Minimize Inventory Cost

Batch sizing strategy in the manufacturing system has significant impacts on the production performance. In the previous research studies, researchers proposed complicated techniques such as optimization models, simulation, queuing theory, and complex algorithms to solve for the optimal batch size. Using those techniques are difficult for plant managers to calculate for the optimal batch size. Therefore, the closed-form optimal batch size equations are proposed to minimize inventory cost of 2 models. The first model is illustrated when the inventory cost is associated with holding cost but without setup cost. The second model is illustrated when inventory cost is associated with both holding cost and setup cost. Besides the optimal batch size calculation, the value of λ, which is the shadow price of the available setup time, is also solved for sensitivity analysis purpose. Application of the closed-form equation is provided with various parameters applied to different products. The results show that the proposed closed-form equations approach performs well and verifies the effectiveness of the approach

Solving cardinality constrained portfolio optimisation problem using genetic algorithms and ant colony optimisation

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonIn this thesis we consider solution approaches for the index tacking problem, in which we aim to reproduces the performance of a market index without purchasing all of the stocks that constitute the index. We solve the problem using three different solution approaches: Mixed Integer Programming (MIP), Genetic Algorithms (GAs), and Ant-colony Optimization (ACO) Algorithm by limiting the number of stocks that can be held. Each index is also assigned with different cardinalities to examine the change to the solution values. All of the solution approaches are tested by considering eight market indices. The smallest data set only consists of 31 stocks whereas the largest data set includes over 2000 stocks. The computational results from the MIP are used as the benchmark to measure the performance of the other solution approaches. The Computational results are presented for different solution approaches and conclusions are given. Finally, we implement post analysis and investigate the best tracking portfolios achieved from the three solution approaches. We summarise the findings of the investigation, and in turn, we further improve some of the algorithms. As the formulations of these problems are mixed-integer linear programs, we use the solver ‘Cplex’ to solve the problems. All of the programming is coded in AMPL

Economic Design of X-bar Control Chart by Ant Colony Optimization

Control charts are widely employed to monitor and maintain the statistical control of a process. Designing a control chart involves selecting a sample size, sample frequency and control limits for the control chart. The costs of sampling and testing, cost of detecting the out-of-control signal and possibly correcting it, and the cost of non-conforming items reaching the consumer give the control chart an economic aspect. In 1956, Duncan developed a Loss Cost Function for X-bar control chart with single assignable cause. The function has to be optimized using a non-conventional optimization technique. In this project, Ant Colony Optimization (ACO) has been employed to optimize Duncan’s Loss Cost Function. Ants while searching for food deposit a chemical pheromone on their way back. The amount of pheromone deposited will be dependent on the quality and quantity of food. As the time progresses the ants become selective in choosing the path depending upon the pheromone deposited. Eventually, this leads the ants to choose the best possible path. An algorithm based on the traditional Ant Colony Optimisation technique developed by Niaki and Ershadi has been applied to the economic model of Duncan. The results were found to be on par with the results obtained by employing other non-conventional optimization techniques such as Genetic Algorithm

Ausgewählte Patientenpfade für das internetbasierende multiple Krankenhausplanspiel COREmain Hospital

Aufgabenstellung dieser Diplomarbeit war es elf ausgewählte Patientenpfade für das internetbasierende multiple Krankenhausplanspiel COREmain hospital zu beschreiben. Die entsprechenden Daten wurden im Krankenhaus der Barmherzigen Schwestern und im St. Josef Spital erhoben. In den ersten beiden Kapiteln wird bestehende Literatur zum Thema klinische Patientenpfade aufgearbeitet. Im dritten Kapitel wird auf bisherige Erfahrungen in der Verwendung von Patientenpfaden in der Palliativpflege und im mentalen Gesundheitswesen eingegangen. In Kapitel 4 wird der Einfluss klinischer Patientenpfade auf medizinische Abweichungen und Fehltritte und die entsprechenden Ergebnisse von einer dazu durchgeführten Studie abgehandelt. Weiters wird näher auf den Einfluss auf postoperative Krankenhausaufenthalte und auf das Pflegepersonal eingegangen. Dabei werden auch kritische Gesichtspunkte angeführt. Der Hauptteil dieser Arbeit beginnt mit Kapitel 5, da hier die Ergebnisse der Datenerhebung dargestellt werden. Zunächst werden alle Krankheiten bzw. jeder chirurgischer Eingriff der Patientenpfade erläutert. Danach kommt es zu einer genauen Darstellung der Ergebnisse der Datenerhebung bezüglich der ausgewählten Patientenpfade. Besondere Auffälligkeiten, Gemeinsamkeiten und Standards werden herausgearbeitet. Die beiden Pfade Herzinfarkt und Schulter werden im Detail beschrieben und graphisch dargestellt werden. Eine Übersichtstabelle über alle bildgebenden Diagnosen zeigt auf einen Blick die jeweiligen Untersuchungen pro Pfad und gibt an ob es sich um Mehrfach- oder Einzeluntersuchungen handelt. Kapitel 6 geht auf die Diagnosetechnologien der bildgebenden Diagnostik der Patientenpfade ein und zeigt sowohl allgemein als auch pfadspezifisch welche Geräte für welche Untersuchung notwendig sind. 62 Das letzte Kapitel ist allen für das Planspiel relevanten Kosten gewidmet. Fixe und variable Kosten bezüglich bildgebender Diagnostik, Operation und Personal werden beschrieben. In weiterer Folge werden auch die LKF-Daten aller ausgewählten Patientenpfade beschrieben und erläutert

Propuesta de solución al problema de generación de trayectorias de tiempo mínimo para un brazo manipulador de seis grados de libertad mediante un aplicativo basado en una trayectoria específica en un ambiente simulado

Ingeniero (a) IndustrialPregrad

Performance management within the NHS

A performance measurement (PM) system should exemplify an organisation’s activities, so it can learn and adapt based on its assessment (Otley, 1999; Adler, 2011; Agostino & Arnaboldi, 2012). This paper investigates ‘to what extent NHS performance can be measured’ in the confines of the Accident and Emergency (A&E) department, at East Lancashire Hospitals NHS Trust. The NHS constitution stipulates ‘95% of patients should be seen and discharged within 4-hours’; hence, this is widely regarded as the ‘key metric’ of A&E performance (The King's Fund, 2016; NHS England, 2013). Since 2013, performance across all areas of health and social care in England, is externally regulated by the Care Quality Commission (CQC, 2015). In 2015/16 ELHT’s emergency services treated over 185,000 patients, placing it in the top-twenty busiest units in the country. Unfortunately, its 4-hour target for the same period was 92.5% and its emergency services were classified as ‘requiring improvement’ by the CQC (HSCIC, 2016; CQC, 2014). Literature relating to performance was critically reviewed, alongside theories of organisational effectiveness (OE). The CQC’s performance regulatory framework was appraised against theoretical models and considered to support PM from an ‘internal process’ perspective (of OE). Conversely, A&E was deemed to align with an ‘open systems’ model i.e. its individuals, groups, processes and interactions are interconnected with the rest of the hospital and the external environment (Stacey & Mowles, 2016). After evaluating various models of ‘open systems’, key components of A&E performance were aggregated and conceptualised into an appropriate framework. Subsequently, research was undertaken in the practical setting to identify areas for improvement. A critical realist research philosophy was applied to a case study design, which incorporated self-completion questionnaires, semi-structured interviews and secondary data collection methods. Research identified some good practices, particularly in relation to A&E’s internal processes i.e. policies and procedures. Other areas included improvements in competency training and medical device technologies. Staff’s professionalism and sense of purpose to providing exceptional care was also very strong. This mood was offset by a sense of disengagement from the organisation that echoed through the factors of the conceptual framework, leading to the following recommendations: r einforce vision and values to A&E staff; create a bespoke A&E mission statement; review A&E leadership structure and training programme; budget training for senior A&E clinical staff; r oll-out of e-Rostering training; u pdate of job descriptions against workplace demands; review of appraisal process; upgrade of IT systems. An area for further research was uncovered relating to producing a standardised ‘A&E coefficient’, which captures all elements of open systems performance, allowing fair comparison for A&E departments across the country

Minimax estimation of the mode of functional data

Wir untersuchen den Modalwert einer Verteilung, die auf einem Funktionenraum wie etwa dem Raum integrierbarer Funktionen definiert ist. Die Definition des Modalwerts basiert auf Small-Ball-Wahrscheinlichkeiten. Wir benutzen Entropiemethoden wie etwa endliche Überdeckungen für die Definition eines Modalwertschätzers und die Beschreibung seines asymptotischen Verhaltens. Wir zeigen die starke Konsistenz und ermitteln die optimale Konvergenzrate für eine Klasse von Verteilungen, deren Modalwerte in einer totalbeschränkten Teilmenge des Funktionenraums liegen.We investigate the mode of a distribution defined on a function space, e.g. the space of integrable functions. We give a definition of the mode using small ball probabilities. We use entropy methods, e.g. finite covers, to define an estimator of the mode and to deduce its asymptotic behaviour. We show strong consistency and continue to derive the optimal rate of convergence over a class of distributions whose modes are contained in a totally bounded subset of the function space

Cost Risk Management for a Small to Medium-sized Enterprise in the Cladding Industry

To research the management of risk and cost in the cladding industry, this work has evaluated current practice and deficiencies, concentrating on the lack of integration or standardisation resulting in inaccurate cost estimates, unacceptable risks and loss of profit in cladding manufacture. The research presents an approach for integrating process- and technology-orientated improvements into a knowledge-based model to improve a cladding manufacturing SME’s performance. The research also presents a management method for the selection, integration, control and implementation of this approach. Controlling data transfer between systems produces a knowledge-based model, allowing cladding industry designers and estimators to take more accurate decisions, with the objective of reducing risk and improving company profitability. This model, with the addition of external supply chain elements, is a management framework, which can be termed an agile manufacturing system. The development of this framework has raised the following data certainty questions: • What is the measured uncertainty of that data? • How can the industry control and structure high data volumes transferred between systems to produce more accurate cost models? The answers to these questions were found by applying a structured methodology for the selection, integration and control of technology in the cladding industry, but involving the human factor. In this approach, the principle of entropy was adopted to measure data uncertainty. The structured methodology was made possible by a new categorisation into Innovative, Standard and Semi-Standard cladding projects. The research applied this structured methodology, combining qualitative and quantitative methods for validating assumptions, to a cladding industry SME case-study. The case-study investigated the validity of real cost and project data and calculated data uncertainty for specific projects, categorised as described, using a risk factor percentage predicted on entropy principles, based on historical data fed back from the SME’s ERP system. This risk factor approach was similar to that previously used in the insurance and banking industries. The risk percentage formulae used were based on assumptions extracted from qualitative and quantitative methods applied to the SME, its partner companies and industry specialists. Assumptions about the gross margins for UK metal cladding projects formed part of the risk percentage formulae. The results of this case-study found that gross margins varied from 5% in standard projects to 40% in the Innovative projects. An entropy scale was proposed as a basis for comparing risk calculation results, with the highest entropy equalling 100%, signifying the highest risk possible. It was found that risk rises in the case-study were from 23% for Standard to 93% for Innovative projects. This principle of a risk factor percentage was tested in the UK cladding manufacturer SME case-study and its value to the SME was demonstrated.

Food industry supply chain planning with product quality indicators

Quantitative supply chain modelling has contributed substantially to a number of fields, such as the automotive industry, logistics and computer hardware. The inherent methods and optimisation techniques could also be explored in relation to the food industry in order to offer potential benefits. One of the major issues of the food industry is to overcome supply seasonality and on-shelf demand. On the shelf demand is the consumer’s in store demand which could also be seasonal. Objective of this work is to add flexibility to seasonal products (i.e. soup) in order to meet the on-shelf demand. In order to achieve this, a preparation process is introduced and integrated into the manufacturing system. This process increases the shelf-life of raw materials before starting the production process. This process, however, affects the quality of fresh raw materials and requires energy. Therefore, a supply chain model is developed, which is based on the link between the quality of the raw material and the processing conditions, which have an effect on the process’ energy consumption and on the overall product quality. It is challenging to quantify the quality by looking at the processing conditions (degrees of freedom) and by linking it with energy in order to control and optimise the quality and energy consumption for each product. The degrees of freedom are defined differently for each process and state. Therefore, the developed model could be applied to all states and processes in order to generate an optimum solution. Moreover, based on the developed model, we have determined key factors in the whole chain, which are most likely to affect the product quality and consequently overall demand. There are two main quality indicator classes to be optimised, which are both considered in the model: static and time dependent indicators. Also, this work considers three different preparation processes – the air-dry, freeze-dry and freezing process – in order to increase the shelf-life of fresh raw materials and to add flexibility to them. A model based on the interrelationship between the quality and the processing conditions has been developed. This new methodology simplifies and enables the model to find the optimum processing conditions in order to obtain optimum quality across all quality indicators, whilst ensuring minimum energy consumption. This model is later integrated into the supply chain system, where it generates optimum solutions, which are then fed into the supply chain model. The supply chain model optimises the quality in terms of customer satisfaction, energy consumption and wastage of the system linked to environmental issues, and cost, so that the final products are more economical. In this system, both the manufacturing and inventory systems are optimised. This model is later implemented with a real world industrial case study (provided by the industrial collaborator). Two case studies are considered (soya milk and soup) and interestingly enough only one of them (soup) corresponds with this model. The advantage of this model is that it compares the two systems and then establishes which system generates an optimum end product.Open Acces