A system dynamics model of employees’ performance

Employee performance is dynamic and can have great impact on the overall performance of any company and its sustainability. A number of factors that can be controlled by the company can affect the employees’ performance. The present paper starts with a thorough literature review for identifying these key driving in order to develop a system dynamics models that will be able to assess different improvement scenarios and initiatives. Based on causal loop diagrams, stock and flow diagrams are developed and solved using system dynamics theory. The model developed can be used for organizations to assess the impact of different improvement initiatives

Employee performance modelling using system dynamics

Employee performance is something dynamic, but can have great impact on the overall performance of any company. This is understood by companies and human resource management departments are responsible for measuring the performance of the employees, and come up with ideas on how to improve this constantly. Such practices include training of employees, providing initiatives such as bonuses and day offs. Furthermore, the literature review has highlighted that leadership style can have a great impact as well. Looking in the literature of employee performance, it was clear as well that there has not been a model that can be used for predicting the impact of such initiatives from systems point of view. So the initial aim was to develop such a model that can help manufacturing companies better handle the dynamic nature of employee performance and if possible help with the decision making when deciding which initiatives to be introduced. The literature review was focused in identifying the factors that have an impact on the employee performance and their possible interrelations. Then the best modelling approach was investigated. Modelling techniques such as discrete event simulation, agent based modelling and system dynamics were considered, with the latter selected at the end as the focus is on the impact of the change of policies and not the individual employees who cannot be modelled due to the random way of their behaviour. System dynamics models were developed based on this analysis and collecting data protocols were formulated for collecting information from companies. The models were validated in two companies in UAE. They can predict the impact that specific changes in policies will have in the employee performance and can guide the companies about what changes they should introduceManufacturin

Lean manufacturing implementation framework based on change management theory and interpretive structural modelling.

Lean management focuses in reducing waste and improve the efficiency of companies. Although in many instances, what is proposed by lean philosophy sounds like common sense, companies do struggle with implementing lean principles. The current research presents a novel framework developed in order to support the lean transformation for manufacturing companies. The framework is based on the change management theory and interpretive structural models. The proposed framework was validated in the United Arabic Emirates (UAE) manufacturing sector. The framework is composed of two main parts, a change transformation approach based on Kotter’s leading change model, and a roadmap for implementing lean tools. The framework proposed was validated using experts’ opinion. The manufacturing sector in UAE is mostly composed of Small and Medium Enterprises, and as such they face a number of challenges when they attempt introduction of lean manufacturing. A questionnaire has been developed for assessing the status of lean manufacturing in the UAE. The level of understanding of lean principles and lean techniques and methods is assessed. The drivers promoting lean thinking and the barriers in the implementation are investigated. The analysis of the responses is currently undertaken. Interpretive structural models (ISM) were also developed for understanding the relationships between the critical success variables and the barriers when implementing lean. The ISM model fed to the lean implementation framework developed. The results and overall feedback from the validation reflected a high level of acceptance of the framework structure and approach. The novel framework has the capability to improve the lean implementation process.PhD in Manufacturin

Optimizing transportation systems and logistics network configurations : From biased-randomized algorithms to fuzzy simheuristics

242 páginasTransportation and logistics (T&L) are currently highly relevant functions in any competitive industry. Locating facilities or distributing goods to hundreds or thousands of customers are activities with a high degree of complexity, regardless of whether facilities and customers are placed all over the globe or in the same city. A countless number of alternative strategic, tactical, and operational decisions can be made in T&L systems; hence, reaching an optimal solution –e.g., a solution with the minimum cost or the maximum profit– is a really difficult challenge, even by the most powerful existing computers. Approximate methods, such as heuristics, metaheuristics, and simheuristics, are then proposed to solve T&L problems. They do not guarantee optimal results, but they yield good solutions in short computational times. These characteristics become even more important when considering uncertainty conditions, since they increase T&L problems’ complexity. Modeling uncertainty implies to introduce complex mathematical formulas and procedures, however, the model realism increases and, therefore, also its reliability to represent real world situations. Stochastic approaches, which require the use of probability distributions, are one of the most employed approaches to model uncertain parameters. Alternatively, if the real world does not provide enough information to reliably estimate a probability distribution, then fuzzy logic approaches become an alternative to model uncertainty. Hence, the main objective of this thesis is to design hybrid algorithms that combine fuzzy and stochastic simulation with approximate and exact methods to solve T&L problems considering operational, tactical, and strategic decision levels. This thesis is organized following a layered structure, in which each introduced layer enriches the previous one.El transporte y la logística (T&L) son actualmente funciones de gran relevancia en cual quier industria competitiva. La localización de instalaciones o la distribución de mercancías a cientos o miles de clientes son actividades con un alto grado de complejidad, indepen dientemente de si las instalaciones y los clientes se encuentran en todo el mundo o en la misma ciudad. En los sistemas de T&L se pueden tomar un sinnúmero de decisiones al ternativas estratégicas, tácticas y operativas; por lo tanto, llegar a una solución óptima –por ejemplo, una solución con el mínimo costo o la máxima utilidad– es un desafío realmente di fícil, incluso para las computadoras más potentes que existen hoy en día. Así pues, métodos aproximados, tales como heurísticas, metaheurísticas y simheurísticas, son propuestos para resolver problemas de T&L. Estos métodos no garantizan resultados óptimos, pero ofrecen buenas soluciones en tiempos computacionales cortos. Estas características se vuelven aún más importantes cuando se consideran condiciones de incertidumbre, ya que estas aumen tan la complejidad de los problemas de T&L. Modelar la incertidumbre implica introducir fórmulas y procedimientos matemáticos complejos, sin embargo, el realismo del modelo aumenta y, por lo tanto, también su confiabilidad para representar situaciones del mundo real. Los enfoques estocásticos, que requieren el uso de distribuciones de probabilidad, son uno de los enfoques más empleados para modelar parámetros inciertos. Alternativamente, si el mundo real no proporciona suficiente información para estimar de manera confiable una distribución de probabilidad, los enfoques que hacen uso de lógica difusa se convier ten en una alternativa para modelar la incertidumbre. Así pues, el objetivo principal de esta tesis es diseñar algoritmos híbridos que combinen simulación difusa y estocástica con métodos aproximados y exactos para resolver problemas de T&L considerando niveles de decisión operativos, tácticos y estratégicos. Esta tesis se organiza siguiendo una estructura por capas, en la que cada capa introducida enriquece a la anterior. Por lo tanto, en primer lugar se exponen heurísticas y metaheurísticas sesgadas-aleatorizadas para resolver proble mas de T&L que solo incluyen parámetros determinísticos. Posteriormente, la simulación Monte Carlo se agrega a estos enfoques para modelar parámetros estocásticos. Por último, se emplean simheurísticas difusas para abordar simultáneamente la incertidumbre difusa y estocástica. Una serie de experimentos numéricos es diseñada para probar los algoritmos propuestos, utilizando instancias de referencia, instancias nuevas e instancias del mundo real. Los resultados obtenidos demuestran la eficiencia de los algoritmos diseñados, tanto en costo como en tiempo, así como su confiabilidad para resolver problemas realistas que incluyen incertidumbre y múltiples restricciones y condiciones que enriquecen todos los problemas abordados.Doctorado en Logística y Gestión de Cadenas de SuministrosDoctor en Logística y Gestión de Cadenas de Suministro

Utilization of research results on forage and agricultural by-product materials as animal feed resources in Africa. Proceedings of the first joint workshop

Presents and discusses research results on feed resources, agroindustrial by-products utilisation, forage production, use of crop residues, dairy feeding systems, feeding strategies, introduction and adoption of improved forage technologies, nutritive value of different forages, effects of management on animal performance, effect of supplements on feed utilisation, potential of agricultural by-products as animal feeds, and effects of management on pasture grasses & legumes; and evaluates the utilisation of these results by smallholders

K-State graduate catalog, 1993-1995

Course catalogs were published under the following titles: Catalogue of the officers and students of the Kansas State Agricultural College, with a brief history of the institution, 1st (1863/4); Annual catalogue of the officers and students of the Kansas State Agricultural College for, 2nd (1864/5)-4th (1868/9); Catalogue of the officers and students of the Kansas State Agricultural College for the year, 1869-1871/2; Hand-book of the Kansas State Agricultural College, Manhattan, Kansas, 1873/4; Biennial catalogue of the Kansas State Agricultural College, Manhattan, Kansas, calendar years, 1875/77; Catalogue of the State Agricultural College of Kansas, 1877/80-1896/97; Annual catalogue of the officers, students and graduates of the Kansas State Agricultural College, Manhattan, 35th (1897/98)-46th (1908/09); Catalogue, 47th (1909/10)-67th (1929/30); Complete catalogue number, 68th (1930/31)-81st (1943/1944); Catalogue, 1945/1946-1948/1949?; General catalogue, 1949/1950?-1958/1960; General catalog, 1960/1962-1990/1992. Course catalogs then split into undergraduate and graduate catalogs respectively: K-State undergraduate catalog, 1992/1994- ; K-State graduate catalog, 1993/1995-Citation: Kansas State University. (1993). K-State graduate catalog, 1993-1995. Manhattan, KS: Kansas State University.Call number: LD2668.A11711 K78

General catalog, 1984-85

Course catalogs were published under the following titles: Catalogue of the officers and students of the Kansas State Agricultural College, with a brief history of the institution, 1st (1863/4); Annual catalogue of the officers and students of the Kansas State Agricultural College for, 2nd (1864/5)-4th (1868/9); Catalogue of the officers and students of the Kansas State Agricultural College for the year, 1869-1871/2; Hand-book of the Kansas State Agricultural College, Manhattan, Kansas, 1873/4; Biennial catalogue of the Kansas State Agricultural College, Manhattan, Kansas, calendar years, 1875/77; Catalogue of the State Agricultural College of Kansas, 1877/80-1896/97; Annual catalogue of the officers, students and graduates of the Kansas State Agricultural College, Manhattan, 35th (1897/98)-46th (1908/09); Catalogue, 47th (1909/10)-67th (1929/30); Complete catalogue number, 68th (1930/31)-81st (1943/1944); Catalogue, 1945/1946-1948/1949?; General catalogue, 1949/1950?-1958/1960; General catalog, 1960/1962-1990/1992. Course catalogs then split into undergraduate and graduate catalogs respectively: K-State undergraduate catalog, 1992/1994- ; K-State graduate catalog, 1993/1995-Citation: Kansas State University. (1984). General catalog, 1984-85. Manhattan, KS: Kansas State University.Call number: LD2668 .A24