Modeling and measuring organizational renewal capability

Globalization and new information technologies mean that organizations have to face world-wide competition in rapidly transforming, unpredictable environments, and thus the ability to constantly generate novel and improved products, services and processes has become quintessential for organizational success. Performance in turbulent environments is, above all, influenced by the organization's capability for renewal. Renewal capability consists of the ability of the organization to replicate, adapt, develop and change its assets, capabilities and strategies. An organization with a high renewal capability can sustain its current success factors while at the same time building new strengths for the future. This capability does not only mean that the organization is able to respond to today's challenges and to keep up with the changes in its environment, but also that it can actas a forerunner by creating innovations, both at the tactical and strategic levels of operation and thereby change the rules of the market. However, even though it is widely agreed that the dynamic capability for continuous learning, development and renewal is a major source of competitive advantage, there is no widely shared view on how organizational renewal capability should be defined, and the field is characterized by a plethora of concepts and definitions. Furthermore,there is a lack of methods for systematically assessing organizational renewal capability. The dissertation aims to bridge these gaps in the existing research by constructing an integrative theoretical framework for organizational renewal capability and by presenting a method for modeling and measuring this capability. The viability of the measurement tool is demonstrated in several contexts, andthe framework is also applied to assess renewal in inter-organizational networks. In this dissertation, organizational renewal capability is examined by drawing on three complimentary theoretical perspectives: knowledge management, strategic management and intellectual capital. The knowledge management perspective considers knowledge as inherently social and activity-based, and focuses on the organizational processes associated with its application and development. Within this framework, organizational renewal capability is understood as the capacity for flexible knowledge integration and creation. The strategic management perspective, on the other hand, approaches knowledge in organizations from the standpoint of its implications for the creation of competitive advantage. In this approach, organizational renewal is framed as the dynamic capability of firms. The intellectual capital perspective is focused on exploring how intangible assets can be measured, reported and communicated. From this vantage point, renewal capability is comprehended as the dynamic dimension of intellectual capital, which consists of the capability to maintain, modify and create knowledge assets. Each of the perspectives significantly contributes to the understanding of organizationalrenewal capability, and the integrative approach presented in this dissertationcontributes to the individual perspectives as well as to the understanding of organizational renewal capability as a whole.

Modeling of residual stresses and distortion due to welding in fillet welds

Welding has a growing role in modern world manufacturing. Welding joints are extensively used from pipes to aerospace industries. Prediction of welding residual stresses and distortions is necessary for accurate evaluation of fillet welds in relation to design and safety conditions. Residual stresses may be beneficial or detrimental, depending whether they are tensile or compressive and the loading. They directly affect the fatigue life of the weld by impacting crack growth rate. Beside theoretical background of residual stresses this study calculates residual stresses and deformations due to localized heating by welding process and subsequent rapid cooling in fillet welds. Validated methods are required for this purpose due to complexity of process, localized heating, temperature dependence of material properties and heat source. In this research both empirical and simulation methods were used for the analysis of welded joints. Finite element simulation has become a popular tool of prediction of welding residual stresses and distortion. Three different cases with and without preload have been modeled during this study. Thermal heat load set is used by calculating heat flux from the given heat input energy. First the linear and then nonlinear material behavior model is modeled for calculation of residual stresses. Experimental work is done to calculate the stresses empirically. The results from both the methods are compared to check their reliability. Residual stresses can have a significant effect on fatigue performance of the welded joints made of high strength steel. Both initial residual stress state and subsequent residual stress relaxation need to be considered for accurate description of fatigue behavior. Tensile residual stresses are detrimental and will reduce the fatigue life and compressive residual stresses will increase it. The residual stresses follow the yield strength of base or filler material and the components made of high strength steel are typically thin, where the role of distortion is emphasizing.

Modeling of burden distribution in the blast furnace

The blast furnace is the main ironmaking production unit in the world which converts iron ore with coke and hot blast into liquid iron, hot metal, which is used for steelmaking. The furnace acts as a counter-current reactor charged with layers of raw material of very different gas permeability. The arrangement of these layers, or burden distribution, is the most important factor influencing the gas flow conditions inside the furnace, which dictate the efficiency of the heat transfer and reduction processes. For proper control the furnace operators should know the overall conditions in the furnace and be able to predict how control actions affect the state of the furnace. However, due to high temperatures and pressure, hostile atmosphere and mechanical wear it is very difficult to measure internal variables. Instead, the operators have to rely extensively on measurements obtained at the boundaries of the furnace and make their decisions on the basis of heuristic rules and results from mathematical models. It is particularly difficult to understand the distribution of the burden materials because of the complex behavior of the particulate materials during charging. The aim of this doctoral thesis is to clarify some aspects of burden distribution and to develop tools that can aid the decision-making process in the control of the burden and gas distribution in the blast furnace. A relatively simple mathematical model was created for simulation of the distribution of the burden material with a bell-less top charging system. The model developed is fast and it can therefore be used by the operators to gain understanding of the formation of layers for different charging programs. The results were verified by findings from charging experiments using a small-scale charging rig at the laboratory. A basic gas flow model was developed which utilized the results of the burden distribution model to estimate the gas permeability of the upper part of the blast furnace. This combined formulation for gas and burden distribution made it possible to implement a search for the best combination of charging parameters to achieve a target gas temperature distribution. As this mathematical task is discontinuous and non-differentiable, a genetic algorithm was applied to solve the optimization problem. It was demonstrated that the method was able to evolve optimal charging programs that fulfilled the target conditions. Even though the burden distribution model provides information about the layer structure, it neglects some effects which influence the results, such as mixed layer formation and coke collapse. A more accurate numerical method for studying particle mechanics, the Discrete Element Method (DEM), was used to study some aspects of the charging process more closely. Model charging programs were simulated using DEM and compared with the results from small-scale experiments. The mixed layer was defined and the voidage of mixed layers was estimated. The mixed layer was found to have about 12% less voidage than layers of the individual burden components. Finally, a model for predicting the extent of coke collapse when heavier pellets are charged over a layer of lighter coke particles was formulated based on slope stability theory, and was used to update the coke layer distribution after charging in the mathematical model. In designing this revision, results from DEM simulations and charging experiments for some charging programs were used. The findings from the coke collapse analysis can be used to design charging programs with more stable coke layers.

The Middle East in the American quest for world order : ideas of power, economics, and social development in United States foreign policy, 1953-1961

Doctoral dissertation, University of Tampere

A conspectus on estimating function theory and its applicability to recurrent modeling issues in forest biometry

Summary

Modeling Forest Growth with Management Data: A Matrix Approach for the Italian Alps

Summary