Analytical Approximations to Predict Performance Measures of Manufacturing Systems with Job Failures and Parallel Processing

Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others.

Performance of a single liquid column damper for the control of dynamic responses of a tension leg platform

Tuned liquid column dampers have been proved to be successful in mitigating the dynamic responses of civil infrastructure. There have been some recent applications of this concept on wind turbines and this passive control system can help to mitigate responses of offshore floating platforms and wave devices. The control of dynamic responses of these devices is important for reducing loads on structural elements and facilitating operations and maintenance (O&M) activities. This paper outlines the use of a tuned single liquid column damper for the control of a tension leg platform supported wind turbine. Theoretical studies were carried out and a scaled model was tested in a wave basin to assess the performance of the damper. The tests on the model presented in this paper correspond to a platform with a very low natural frequency for surge, sway and yaw motions. For practical purposes, it was not possible to tune the liquid damper exactly to this frequency. The consequent approach taken and the efficiency of such approach are presented in this paper. Responses to waves of a single frequency are investigated along with responses obtained from wave spectra characterising typical sea states. The extent of control is quantified using peak and root mean squared dynamic responses respectively. The tests present some guidelines and challenges for testing scaled devices in relation to including response control mechanisms. Additionally, the results provide a basis for dictating future research on tuned liquid column damper based control on floating platforms.

A Capability Maturity Model to Assess Supply Chain Performance

In an overcapacity world, where the customers can choose from many similar products to satisfy their needs, enterprises are looking for new approaches and tools that can help them not only to maintain, but also to increase their competitive edge. Innovation, flexibility, quality, and service excellence are required to, at the very least, survive the on-going transition that industry is experiencing from mass production to mass customization. In order to help these enterprises, this research develops a Supply Chain Capability Maturity Model named S(CM)2. The Supply Chain Capability Maturity Model is intended to model, analyze, and improve the supply chain management operations of an enterprise. The Supply Chain Capability Maturity Model provides a clear roadmap for enterprise improvement, covering multiple views and abstraction levels of the supply chain, and provides tools to aid the firm in making improvements. The principal research tool applied is the Delphi method, which systematically gathered the knowledge and experience of eighty eight experts in Mexico. The model is validated using a case study and interviews with experts in supply chain management. The resulting contribution is a holistic model of the supply chain integrating multiple perspectives, and providing a systematic procedure for the improvement of a company’s supply chain operations.

Cloud Benchmarking For Maximising Performance of Scientific Applications

How can applications be deployed on the cloud to achieve maximum performance? This question is challenging to address with the availability of a wide variety of cloud Virtual Machines (VMs) with different performance capabilities. The research reported in this paper addresses the above question by proposing a six step benchmarking methodology in which a user provides a set of weights that indicate how important memory, local communication, computation and storage related operations are to an application. The user can either provide a set of four abstract weights or eight fine grain weights based on the knowledge of the application. The weights along with benchmarking data collected from the cloud are used to generate a set of two rankings - one based only on the performance of the VMs and the other takes both performance and costs into account. The rankings are validated on three case study applications using two validation techniques. The case studies on a set of experimental VMs highlight that maximum performance can be achieved by the three top ranked VMs and maximum performance in a cost-effective manner is achieved by at least one of the top three ranked VMs produced by the methodology.

The role of Lean at the interface with between operations management and applied services within a large aerospace organisation: a boundary spanning perspective

Increased complexity in large design and manufacturing organisations requires improvements at the operations management (OM)–applied service (AS) interface areas to improve project effectiveness. The aim of this paper is explore the role of Lean in improving the longitudinal efficiency of the OM–AS interface within a large aerospace organisation using Lean principles and boundary spanning theory. The methodology was an exploratory longitudinal case approach including exploratory interviews (n = 21), focus groups (n = 2), facilitated action-research workshops (n = 2) and two trials or experiments using longitudinal data involving both OM and AS personnel working at the interface. The findings draw upon Lean principles and boundary spanning theory to guide and interpret the findings. It was found that misinterpretation, and forced implementation, of OM-based Lean terminology and practice in the OM–AS interface space led to delays and misplaced resources. Rather both OM and AS staff were challenged to develop a cross boundary understanding of Lean-based boundary (knowledge) objects in interpreting OM requests. The longitudinal findings from the experiments showed that the development of Lean Performance measurements and lean Value Stream constructs was more successful when these Lean constructs were treated as boundary (knowledge) objects requiring transformation over time to orchestrate improved effectiveness and in leading to consistent terminology and understanding between the OM–AS boundary spanning team.

Highway Performance and Time-Sensitive Industries, 1998

This report addresses delays to freight shippers. Although the focus is on just-in-time (JIT) businesses, the authors also note that non JIT businesses also suffer delays that impact their productivity. The table of contents lists the following headings: chapter 1 - introduction - a trial application: the Des Moines metropolitan area; structure of the report; chapter 2 - reliability at the forefront of freight transport demand - manufacturing and inventory; just-in-time operations in the U.S.; transportation consequences; summary; chapter 3 - JIT operations in Iowa - survey and sample; trucking activity and service; just-in-time truck transportation in Iowa; assessment of factors affecting truck transportation service; summary and conclusions; chapter 4 - travel time uncertainty induced by incidents - a probabilistic model for incident occurrences and durations; calculation of delay; trial application; conclusions; and chapter 5 - conclusions and recommendations - conclusions; recommendations.

Error Recovery Performance: The Impact of Leader Behavioral Integrity and Job Satisfaction

This article introduces the concept of error recovery performance, followed by the development and validation of an instrument to measure it. The first objective of this article is to broaden the current concept of service recovery to be relevant to the back-of-house operations. The second objective is to examine the influence of leader behavioral integrity (BI) on error recovery performance. Moreover, the study examines the mediating effect of job satisfaction between BI and error recovery performance. Finally, the study links error management performance with work-unit effectiveness. Data for Study 1 were collected from 369 hotel employees in Turkey. The same relationships were tested again in Study 2 to validate the findings of Study 1 with a different sample. Data for Study 2 were collected from 33 departmental managers from the same hotels. Linear regression analysis was used to test the direct effects. The mediating effects were tested using the mediation test suggested by Preacher and Hayes. In addition, in Study 2, general managers of the hotels were asked to rate the effectiveness of each manager and their respective department. Results from Study 1 indicate that BI drives error recovery performance, and this impact is mediated by employee job satisfaction. Results of Study 2 confirm this model and finds further that managers’ self-rated error recovery performance was associated with their general managers’ assessment of their deliverables and of their department’s overall performance.

Influence of grinding operations on surface integrity and chloride induced stress corrosion cracking of stainless steels

Stainless steels were developed in the early 20th century and are used where both the mechanical properties of steels and corrosion resistance are required. There is continuous research to allow stainless steel components to be produced in a more economical way and be used in more harsh environments. A necessary component in this effort is to correlate the service performance with the production processes. The central theme of this thesis is the mechanical grinding process.  This is commonly used for producing stainless steel components, and results in varied surface properties that will strongly affect their service life. The influence of grinding parameters including abrasive grit size, machine power and grinding lubricant were studied for 304L austenitic stainless steel (Paper II) and 2304 duplex stainless steel (Paper I). Surface integrity was proved to vary significantly with different grinding parameters. Abrasive grit size was found to have the largest influence. Surface defects (deep grooves, smearing, adhesive/cold welding chips and indentations), a highly deformed surface layer up to a few microns in thickness and the generation of high level tensile residual stresses in the surface layer along the grinding direction were observed as the main types of damage when grinding stainless steels. A large degree of residual stress anisotropy is interpreted as being due to mechanical effects dominating over thermal effects. The effect of grinding on stress corrosion cracking behaviour of 304L austenitic stainless steel in a chloride environment was also investigated (Paper III). Depending on the surface conditions, the actual loading by four-point bend was found to deviate from the calculated value using the formula according to ASTM G39 by different amounts. Grinding-induced surface tensile residual stress was suggested as the main factor to cause micro-cracks initiation on the ground surfaces. Grinding along the loading direction was proved to increase the susceptibility to chloride-induced SCC, while grinding perpendicular to the loading direction improved SCC resistance. The knowledge obtained from this work can provide a reference for choosing appropriate grinding parameters when fabricating stainless steel components; and can also be used to help understanding the failure mechanism of ground stainless steel components during service.

Discrete-event Simulation and Optimization to Improve the Performance of a Healthcare System

Thesis (Ph.D.)--University of Washington, 2016-08

Vehicle Distance Threshold for Quayside Operations of Container Terminals

Thesis (Master's)--University of Washington, 2016-08

Development of management accounting practices in energy operations in a forest industry Company

The aim of this master’s thesis was to map the management accounting processes and reporting of an internal service unit. The research was conducted in energy services in a forest industry company. Research questions and the results of the study are highly specific for the case unit although some generalizable features of management accounting in internal service units under shared services were searched. The research was carried out as a qualitative action research and a single case study. Internal benchmarking was used to find best practices from other units and to get a comprehensive understanding of the financial processes of the case company. Empirical data for the study was collected with participant observation, interviews of experts and by exploring internal company documents. A literature review was conducted to outline the subject and to support the study. Although the management accounting processes of the case unit were found to be on a good level, some improvement ideas were presented. Results of the research show that the needs of the customers are in the key role in the processes of an internal service unit. Management accounting and reporting need to support the company strategy and management decision-making. To evaluate the performance of the service unit both financial and non-financial measures are needed.

A Performance Management Framework for Managing Sustainable Collaborative Enterprise Networks

Part 15: Performance Management Frameworks

Improving Resource Management in Virtualized Data Centers using Application Performance Models

The rapid growth of virtualized data centers and cloud hosting services is making the management of physical resources such as CPU, memory, and I/O bandwidth in data center servers increasingly important. Server management now involves dealing with multiple dissimilar applications with varying Service-Level-Agreements (SLAs) and multiple resource dimensions. The multiplicity and diversity of resources and applications are rendering administrative tasks more complex and challenging. This thesis aimed to develop a framework and techniques that would help substantially reduce data center management complexity. We specifically addressed two crucial data center operations. First, we precisely estimated capacity requirements of client virtual machines (VMs) while renting server space in cloud environment. Second, we proposed a systematic process to efficiently allocate physical resources to hosted VMs in a data center. To realize these dual objectives, accurately capturing the effects of resource allocations on application performance is vital. The benefits of accurate application performance modeling are multifold. Cloud users can size their VMs appropriately and pay only for the resources that they need; service providers can also offer a new charging model based on the VMs performance instead of their configured sizes. As a result, clients will pay exactly for the performance they are actually experiencing; on the other hand, administrators will be able to maximize their total revenue by utilizing application performance models and SLAs. This thesis made the following contributions. First, we identified resource control parameters crucial for distributing physical resources and characterizing contention for virtualized applications in a shared hosting environment. Second, we explored several modeling techniques and confirmed the suitability of two machine learning tools, Artificial Neural Network and Support Vector Machine, to accurately model the performance of virtualized applications. Moreover, we suggested and evaluated modeling optimizations necessary to improve prediction accuracy when using these modeling tools. Third, we presented an approach to optimal VM sizing by employing the performance models we created. Finally, we proposed a revenue-driven resource allocation algorithm which maximizes the SLA-generated revenue for a data center.

The Survival and Stock Performance of Emerging Country Firms in the United States

Many firms from emerging markets flocked to developed countries at high cost with hopes of acquiring strategic assets that are difficult to obtain in home countries. Adequate research has focused on the motivations and strategies of emerging country firms' (ECFs') internationalization, while limited studies have explored their survival in advanced economies years after their venturing abroad. Due to the imprinting effect of home country institutions that inhibit their development outside their home market, ECFs are inclined to hire executives with international background and affiliate to world-wide organizations for the purpose of linking up with the global market, embracing multiple perspectives for strategic decisions, and absorbing the knowledge of foreign markets. However, the effects of such orientation on survival are under limited exploration. Motivated by the discussion above, I explore ECFs’ survival and stock performance in a developed country (U.S.). Applying population ecology, signaling theory and institutional theory, the dissertation investigates the characteristics of ECFs that survived in the developed country (U.S.), tests the impacts of global orientation on their survival, and examines how global-oriented activities (i.e. joining United Nations Global Compact) affect their stock performance. The dissertation is structured in the form of three empirical essays. The first essay explores and compares different characteristics of ECFs and developed country firms (DCFs) that managed to survive in the U.S. The second essay proposes the concept of global orientation, and tests its influences on ECFs’ survival. Employing signaling theory and institutional theory, the third essay investigates stock market reactions to announcements of United Nation Global Compact (UNGC) participation. The dissertation serves to explore the survival of ECFs in the developed country (U.S.) by comparison with DCFs, enriching traditional theories by testing non-traditional arguments in the context of ECFs’ foreign operation, and better informing practitioners operating ECFs about ways of surviving in developed countries and improving stockholders’ confidence in their future growth.

The significant role of third-party logistics (3pl) operators as fosterers of organizational performance in colombian companies

La eliminación de barreras entre países es una consecuencia que llega con la globalización y con los acuerdos de TLC firmados en los últimos años. Esto implica un crecimiento significativo del comercio exterior, lo cual se ve reflejado en un aumento de la complejidad de la cadena de suministro de las empresas. Debido a lo anterior, se hace necesaria la búsqueda de alternativas para obtener altos niveles de productividad y competitividad dentro de las empresas en Colombia, ya que el entorno se ha vuelto cada vez más complejo, saturado de competencia no sólo nacional, sino también internacional. Para mantenerse en una posición competitiva favorable, las compañías deben enfocarse en las actividades que le agregan valor a su negocio, por lo cual una de las alternativas que se están adoptando hoy en día es la tercerización de funciones logísticas a empresas especializadas en el manejo de estos servicios. Tales empresas son los Proveedores de servicios logísticos (LSP), quienes actúan como agentes externos a la organización al gestionar, controlar y proporcionar actividades logísticas en nombre de un contratante. Las actividades realizadas pueden incluir todas o parte de las actividades logísticas, pero como mínimo la gestión y ejecución del transporte y almacenamiento deben estar incluidos (Berglund, 2000). El propósito del documento es analizar el papel de los Operadores Logísticos de Tercer nivel (3PL) como promotores del desempeño organizacional en las empresas colombianas, con el fin de informar a las MIPYMES acerca de los beneficios que se obtienen al trabajar con LSP como un medio para mejorar la posición competitiva del país.