Success of service-intensive manufacturing firms - resource-based view

The main objective of this study is to examine the relationships between resources, competitive advantage and firm success. The study focuses, on one hand, on the financial performance of service-intensive manufac-turing firms against competitors with a lower service intensity and, on the other hand, on the resources as drivers for competitive advantage and success. The purpose of the theoretical part is to link the study in the field of the strategy research. The empirical part of the study is based on the quantitative analyses of the survey data collected from 50 major suppliers of industrial machinery and transportation equipment in Europe and North America. Results indicate that service-intensive manufacturing firms have performed better and their performance has been more stable vis-à-vis their peers. The main resources that differentiate service-intensive manufacturing firms from their non-service intensive competitors are service strategy and service-oriented top management. The analyses on the VRIO resources produced only a limited amount of information and solely service-centred culture appeared to be a rent generating resource.

Algorithmic Solutions for Combinatorial Problems in Resource Management of Manufacturing Environments

This thesis studies the use of heuristic algorithms in a number of combinatorial problems that occur in various resource constrained environments. Such problems occur, for example, in manufacturing, where a restricted number of resources (tools, machines, feeder slots) are needed to perform some operations. Many of these problems turn out to be computationally intractable, and heuristic algorithms are used to provide efficient, yet sub-optimal solutions. The main goal of the present study is to build upon existing methods to create new heuristics that provide improved solutions for some of these problems. All of these problems occur in practice, and one of the motivations of our study was the request for improvements from industrial sources. We approach three different resource constrained problems. The first is the tool switching and loading problem, and occurs especially in the assembly of printed circuit boards. This problem has to be solved when an efficient, yet small primary storage is used to access resources (tools) from a less efficient (but unlimited) secondary storage area. We study various forms of the problem and provide improved heuristics for its solution. Second, the nozzle assignment problem is concerned with selecting a suitable set of vacuum nozzles for the arms of a robotic assembly machine. It turns out that this is a specialized formulation of the MINMAX resource allocation formulation of the apportionment problem and it can be solved efficiently and optimally. We construct an exact algorithm specialized for the nozzle selection and provide a proof of its optimality. Third, the problem of feeder assignment and component tape construction occurs when electronic components are inserted and certain component types cause tape movement delays that can significantly impact the efficiency of printed circuit board assembly. Here, careful selection of component slots in the feeder improves the tape movement speed. We provide a formal proof that this problem is of the same complexity as the turnpike problem (a well studied geometric optimization problem), and provide a heuristic algorithm for this problem.

Library Services in a New Perspective: Unifying Resource Management

Johan Rademakersin esitys Kirjastoverkkopäivillä 26.10.2011.

RDA (Resource Description and Access) – kuvailuohjeiden kansainvälinen ja kansallinen käyttöönotto

Marjatta Autio-Tuulen esitys Kuvailun tiedotuspäivillä Helsingissä 20.3.2013.

Project Resource Management in R&D Public Sector Organization

In R&D organizations multiple projects are executed concurrently. Problems arises in managing shared resources since they are needed by multiple projects simultaneously. The objective of this thesis was to study how the project and resource management could be developed in a public sector R&D organization. The qualitative research was carried out in the Magnetic Measurements section at CERN where the section measures magnets for particle accelerators and builds state of the art measurement devices for various needs. Hence, the R&D and measurement projects are very time consuming and very complex. Based on the previous research and the requirements from the organization the best alter- native for resource management was to build a project management information system. A centralized database was constructed and on top of it was built an application for interacting and visualizing the project data. The application allows handling project data, which works as a basis for resource planning before and during the projects are executed. It is one way to standardize the work-flow of projects, which strengthens the project process. Additionally, it was noted that the inner customer’s database, the measurement system and the new application needed to be integrated. Further integration ensures that the project data is received efficiently from customers and available not only within the application but also during the concrete work. The research results introduced a new integrated application, which centralizes the project information flow with better visibility.

Virtual Runtime Application Partitions for Resource Management in Massively Parallel Architectures

This thesis presents a novel design paradigm, called Virtual Runtime Application Partitions (VRAP), to judiciously utilize the on-chip resources. As the dark silicon era approaches, where the power considerations will allow only a fraction chip to be powered on, judicious resource management will become a key consideration in future designs. Most of the works on resource management treat only the physical components (i.e. computation, communication, and memory blocks) as resources and manipulate the component to application mapping to optimize various parameters (e.g. energy efficiency). To further enhance the optimization potential, in addition to the physical resources we propose to manipulate abstract resources (i.e. voltage/frequency operating point, the fault-tolerance strength, the degree of parallelism, and the configuration architecture). The proposed framework (i.e. VRAP) encapsulates methods, algorithms, and hardware blocks to provide each application with the abstract resources tailored to its needs. To test the efficacy of this concept, we have developed three distinct self adaptive environments: (i) Private Operating Environment (POE), (ii) Private Reliability Environment (PRE), and (iii) Private Configuration Environment (PCE) that collectively ensure that each application meets its deadlines using minimal platform resources. In this work several novel architectural enhancements, algorithms and policies are presented to realize the virtual runtime application partitions efficiently. Considering the future design trends, we have chosen Coarse Grained Reconfigurable Architectures (CGRAs) and Network on Chips (NoCs) to test the feasibility of our approach. Specifically, we have chosen Dynamically Reconfigurable Resource Array (DRRA) and McNoC as the representative CGRA and NoC platforms. The proposed techniques are compared and evaluated using a variety of quantitative experiments. Synthesis and simulation results demonstrate VRAP significantly enhances the energy and power efficiency compared to state of the art.

Adaptive Dynamics of Resource Specialization

Ecological specialization in resource utilization has various facades ranging from nutritional resources via host use of parasites or phytophagous insects to local adaptation in different habitats. Therefore, the evolution of specialization affects the evolution of most other traits, which makes it one of the core issues in the theory of evolution. Hence, the evolution of specialization has gained enormous amounts of research interest, starting already from Darwin’s Origin of species in 1859. Vast majority of the theoretical studies has, however, focused on the mathematically most simple case with well-mixed populations and equilibrium dynamics. This thesis explores the possibilities to extend the evolutionary analysis of resource usage to spatially heterogeneous metapopulation models and to models with non-equilibrium dynamics. These extensions are enabled by the recent advances in the field of adaptive dynamics, which allows for a mechanistic derivation of the invasion-fitness function based on the ecological dynamics. In the evolutionary analyses, special focus is set to the case with two substitutable renewable resources. In this case, the most striking questions are, whether a generalist species is able to coexist with the two specialist species, and can such trimorphic coexistence be attained through natural selection starting from a monomorphic population. This is shown possible both due to spatial heterogeneity and due to non-equilibrium dynamics. In addition, it is shown that chaotic dynamics may sometimes inflict evolutionary suicide or cyclic evolutionary dynamics. Moreover, the relations between various ecological parameters and evolutionary dynamics are investigated. Especially, the relation between specialization and dispersal propensity turns out to be counter-intuitively non-monotonous. This observation served as inspiration to the analysis of joint evolution of dispersal and specialization, which may provide the most natural explanation to the observed coexistence of specialist and generalist species.