Interfirm Information System for Supply Chain Management from the Cloud: An Exploratory Case Study from the Telecom Industry

This study examines the practice of supply chain management problems and the perceived demand information distortion’s (the bullwhip effect) reduction with the interfirm information system, which is delivered as a cloud service to a company operating in the telecommunications industry. The purpose is to shed light in practice that do the interfirm information system have impact on the performance of the supply chain and in particularly the reduction of bullwhip effect. In addition, a holistic case study of the global telecommunications company's supply chain is presented and also the challenges it’s facing, and this study also proposes some measures to improve the situation. The theoretical part consists of the supply chain and its management, as well as increasing the efficiency and introducing the theories and related previous research. In addition, study presents performance metrics for the bullwhip effect detection and tracking. The theoretical part ends in presenting cloud -based business intelligence theoretical framework used in the background of this study. The research strategy is a qualitative case study, supported by quantitative data, which is collected from a telecommunication sector company's databases. Qualitative data were gathered mainly with two open interviews and the e-mail exchange during the development project. In addition, other materials from the company were collected during the project and the company's web site information was also used as the source. The data was collected to a specific case study database in order to increase reliability. The results show that the bullwhip effect can be reduced with the interfirm information system and with the use of CPFR and S&OP models and in particularly combining them to an integrated business planning. According to this study the interfirm information system does not, however, solve all of the supply chain and their effectiveness -related problems, because also the company’s processes and human activities have a major impact.

e-Business and collaboration: A case study of pulp supply chain

This thesis studies how the case company could digitalize its supply chain and what kind of advantages this would create in the light of supply chain efficiency. The case company manufactures several pulp products that are used for paper, fabrics and packaging products by customers worldwide. The paper and pulp industry has been paying more and more attention to increasing supply chain efficiency with new operating and service models made possible by today’s information technology. The main focus of this study is on the supply chain between the case company and its key customers and the goal is to find ways to make the operations between them as efficient as possible. The study relays heavily on collaboration techniques and digitalization technologies. In addition to a theoretical framework, the study includes several empirical studies that offer real-life examples of how these theories and technologies are applied in operating environments similar to the case company. A plan with strategic and operational levels is created according to the findings of the previous sections to support the case company’s future operations. The plan is based on an RFID-supported collaboration model that aims to advance information sharing between the supply chain partners. The time for an RFID-investment is sought to be very optimal and the benefits of such system to be noteworthy, but challenging to measure in monetary terms.

Global Spare Parts Supply Chain Analysis

In today’s global industrial service business, markets are dynamic and finding new ways of value creation towards customers has become more and more challenging. Customer orientation is needed because of the demanding after-sales business which is both quickly changing and stochastic in nature. In after-sales business customers require fast and reliable service for their spare part needs. This thesis objective is to clarify this challenging after-sales business environment and find ways to increase customer satisfaction via balanced measurement system which will help to find possible targets to reduce order cycle times in a large metal and mineral company Outotec (Filters)’ Spare Part Supply business line. In case study, internal documents and data and numerical calculations together with qualitative interviews with different persons in key roles of Spare Part Supply organizations are used to analyze the performance of different processes from the spare parts delivery function. The chosen performance measurement tool is Balanced Scorecard which is slightly modified to suit the lead time study from customer’s perspective better. Findings show that many different processes in spare parts supply are facing different kind of challenges in achieving the lead time levels wanted and that these processes’ problems seem to accumulate. Findings also show that putting effort in supply side challenges and information flows visibility should give the best results.

Adaptive Markov chain Monte Carlo and Bayesian filtering for state space models

This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.

The radio frequency identification technology in the supply chain management: a case of a big logistics company

Nowadays global business trends force the adoption of innovative ICTs into the supply chain management (SCM). Particularly, the RFID technology is on high demand among SCM professionals due to its business advantages such as improving of accuracy and veloc-ity of SCM processes which lead to decrease of operational costs. Nevertheless, a question of the RFID technology impact on the efficiency of warehouse processes in the SCM re-mains open. The goal of the present study is to experiment the possibility of improvement order picking velocity in a warehouse of a big logistics company with the use of the RFID technology. In order to achieve this goal the following objectives have been developed: 1) Defining the scope of the RFID technology applications in the SCM; 2) Justification of the RFID technology impact on the SCM processes; 3) Defining a place of the warehouse order picking process in the SCM; 4) Identification and systematization of existing meth-ods of order picking velocity improvement; 5) Choosing of the study object and gathering of the empirical data about number of orders, number of hours spent per each order line daily during 5 months; 6) Processing and analysis of the empirical data; 7) Conclusion about the impact of the RFID technology on the speed of order picking process. As a result of the research it has been found that the speed of the order picking processes has not been changed as time has gone after the RFID adoption. It has been concluded that in order to achieve a positive effect in the speed of order picking process with the use of the RFID technology it is necessary to simultaneously implement changes in logistics and organizational management in 3PL logistics companies. Practical recommendations have been forwarded to the management of the company for further investigation and procedure.

The Cycle Times of Working Capital: Financial Value Chain Analysis Method

Interest towards working capital management increased among practitioners and researchers because the financial crisis of 2008 caused the deterioration of the general financial situation. The importance of managing working capital effectively increased dramatically during the financial crisis. On one hand, companies highlighted the importance of working capital management as part of short-term financial management to overcome funding difficulties. On the other hand, in academia, it has been highlighted the need to analyze working capital management from a wider perspective namely from the value chain perspective. Previously, academic articles mostly discussed working capital management from a company-centered perspective. The objective of this thesis was to put working capital management in a wider and more academic perspective and present case studies of the value chains of industries as instrumental in theoretical contributions and practical contributions as complementary to theoretical contributions and conclusions. The principal assumption of this thesis is that selffinancing of value chains can be established through effective working capital management. Thus, the thesis introduces the financial value chain analysis method which is employed in the empirical studies. The effectiveness of working capital management of the value chains is studied through the cycle time of working capital. The financial value chain analysis method employed in this study is designed for considering value chain level phenomena. This method provides a holistic picture of the value chain through financial figures. It extends the value chain analysis to the industry level. Working capital management is studied by the cash conversion cycle that measures the length (days) of time a company has funds tied up in working capital, starting from the payment of purchases to the supplier and ending when remittance of sales is received from the customers. The working capital management practices employed in the automotive, pulp and paper and information and communication technology industries have been studied in this research project. Additionally, the Finnish pharmaceutical industry is studied to obtain a deeper understanding of the working capital management of the value chain. The results indicate that the cycle time of working capital is constant in the value chain context over time. The cash conversion cycle of automotive, pulp and paper, and ICT industries are on average 70, 60 and 40 days, respectively. The difference is mainly a consequence of the different cycle time of inventories. The financial crisis of 2008 affected the working capital management of the industries similarly. Both the cycle time of accounts receivable and accounts payable increased between 2008 and 2009. The results suggest that the companies of the automotive, pulp and paper and ICT value chains were not able to self-finance. Results do not indicate the improvement of value chains position in regard to working capital management either. The findings suggest that companies operating in the Finnish pharmaceutical industry are interested in developing their own working capital management, but collaboration with the value chain partners is not considered interesting. Competition no longer occurs between individual companies, but between value chains. Therefore the financial value chain analysis method introduced in this thesis has the potential to support value chains in improving their competitiveness.

The demand-supply balancing process in supply chain management - case mining & metals industry equipment

The aim of this thesis is to search how to match the demand and supply effectively in industrial and project-oriented business environment. The demand-supply balancing process is searched through three different phases: the demand planning and forecasting, synchronization of demand and supply and measurement of the results. The thesis contains a single case study that has been implemented in a company called Outotec. In the case study the demand is planned and forecasted with qualitative (judgmental) forecasting method. The quantitative forecasting methods are searched further to support the demand forecast and long term planning. The sales and operations planning process is used in the synchronization of the demand and supply. The demand forecast is applied in the management of a supply chain of critical unit of elemental analyzer. Different meters on operational and strategic level are proposed for the measurement of performance.

Reporting of Green Supply Chain Management and Industrial Symbiosis

The purpose of this thesis is to examine how the reporting of operations related to green supply chain management and industrial symbiosis has evolved in UPM, Fortum and Kemira within the last ten years. The focus is on the improved operations, which are studied based on annual reports of these companies. The study provides a deeper understanding of the nature of green supply chain management and industrial symbiosis as well as the possibilites that their combination offers. The research is part of the DemaNET research project The study indicates that the environmental regulations and reporting standards have forced the studied companies to report their operations related to green supply chain management and industrial symbiosis more in detail during the last ten years. The operations related to green supply chain management in the studied companies are more common compared to operations related to industrial symbiosis. Often these two operations were also partially integrated, indicating a hybrid model. Even though firms often used hybrid models they still focused mainly on greening the internal operations rather than finding alternative ways for symbiosis outside the organization. The integration of green supply chain management and industrial symbiosis is most likely to occur when mutually beneficial relationships align the interests of all parties, thus resulting in the co-creation of value. The findings suggest that identifying mutual benefits and the flow of by-products are the ones that companies should give more attention to.

Automatic recognition of fish from video sequences

The problem of automatic recognition of the fish from the video sequences is discussed in this Master’s Thesis. This is a very urgent issue for many organizations engaged in fish farming in Finland and Russia because the process of automation control and counting of individual species is turning point in the industry. The difficulties and the specific features of the problem have been identified in order to find a solution and propose some recommendations for the components of the automated fish recognition system. Methods such as background subtraction, Kalman filtering and Viola-Jones method were implemented during this work for detection, tracking and estimation of fish parameters. Both the results of the experiments and the choice of the appropriate methods strongly depend on the quality and the type of a video which is used as an input data. Practical experiments have demonstrated that not all methods can produce good results for real data, whereas on synthetic data they operate satisfactorily.

E-commerce value chain in Russian markets – The role of market specific factors

International e-commerce is still rather new concept and therefore lacks comprehensive research. Different nature of markets and companies has challenged the traditional theories as well as redefined traditional operations. Prior research has mainly concentrated on studying the specific topics as barriers and the choice of international strategy. For this reason, there is a lack of research that comprehensively analyzes the operations of international e-commerce companies. The aim of this study was to increase knowledge on operations of Finnish e-commerce companies in Russia. In order to receive comprehensive knowledge of the operations, research analyzed the internationalization process, the effects of market specific factors to e-commerce and the implementation of various value chain activities of e-commerce. Research focused on examining how companies have seen the peculiarities of Russian markets and how to respond to them. The empiric part of the study was conducted as a qualitative research by interviewing five company representatives and three specialists of international e-commerce and Russian business.The results of this research revealed that having e-commerce in Russia is challenging and requires long term, strategy-based work. E-commerce is assumed to be inherently global business model, but in the case of Russia, numerous e-commerce activities require localization. The most crucial activity to localize is a content and language of content. Even though e-commerce market in Russia has a lot of peculiarities, operating via marketspace decreases the level of bureaucracy and market risk. Despite the challenges, developing e- commerce market in Russia offers a huge potential for companies, whose international strategy needs Russian operation to achieve company goals.

Optimal processing chain for waste power plant

This study is done to examine waste power plant’s optimal processing chain and it is important to consider from several points of view on why one option is better than the other. This is to insure that the right decision is made. Incineration of waste has devel-oped to be one decent option for waste disposal. There are several legislation matters and technical options to consider when starting up a waste power plant. From the tech-niques pretreatment, burner and flue gas cleaning are the biggest ones to consider. The treatment of incineration residues is important since it can be very harmful for the envi-ronment. The actual energy production from waste is not highly efficient and there are several harmful compounds emitted. Recycling of waste before incineration is not very typical and there are not many recycling options for materials that cannot be easily re-cycled to same product. Life cycle assessment is a good option for studying the envi-ronmental effect of the system. It has four phases that are part of the iterative study process. In this study the case environment is a waste power plant. The modeling of the plant is done with GaBi 6 software and the scope is from gate-to-grave. There are three different scenarios, from which the first and second are compared to each other to reach conclusions. Zero scenario is part of the study to demonstrate situation without the power plant. The power plant in this study is recycling some materials in scenario one and in scenario two even more materials and utilize the bottom ash more ways than one. The model has the substitutive processes for the materials when they are not recycled in the plant. The global warming potential results show that scenario one is the best option. The variable costs that have been considered tell the same result. The conclusion is that the waste power plant should not recycle more and utilize bottom ash in a number of ways. The area is not ready for that kind of utilization and production from recycled materials.