Business intelligence – enabling self-service: A case study in a global manufacturing company

Business intelligence (BI) is an information process that includes the activities and applications used to transform business data into valuable business information. Today’s enterprises are collecting detailed data which has increased the available business data drastically. In order to meet changing customer needs and gain competitive advantage businesses try to leverage this information. However, IT departments are struggling to meet the increased amount of reporting needs. Therefore, recent shift in the BI market has been towards empowering business users with self-service BI capabilities. The purpose of this study was to understand how self-service BI could help businesses to meet increased reporting demands. The research problem was approached with an empirical single case study. Qualitative data was gathered with a semi-structured, theme-based interview. The study found out that case company’s BI system was mostly used for group performance reporting. Ad-hoc and business user-driven information needs were mostly fulfilled with self-made tools and manual work. It was felt that necessary business information was not easily available. The concept of self-service BI was perceived to be helpful to meet such reporting needs. However, it was found out that the available data is often too complex for an average user to fully understand. The respondents felt that in order to self-service BI to work, the data has to be simplified and described in a way that it can be understood by the average business user. The results of the study suggest that BI programs struggle in meeting all the information needs of today’s businesses. The concept of self-service BI tries to resolve this problem by allowing users easy self-service access to necessary business information. However, business data is often complex and hard to understand. Self-serviced BI has to overcome this challenge before it can reach its potential benefits.

Business intelligence – enabling self-service: A case study in a global manufacturing company

Business intelligence (BI) is an information process that includes the activities and applications used to transform business data into valuable business information. Today’s enterprises are collecting detailed data which has increased the available business data drastically. In order to meet changing customer needs and gain competitive advantage businesses try to leverage this information. However, IT departments are struggling to meet the increased amount of reporting needs. Therefore, recent shift in the BI market has been towards empowering business users with self-service BI capabilities. The purpose of this study was to understand how self-service BI could help businesses to meet increased reporting demands. The research problem was approached with an empirical single case study. Qualitative data was gathered with a semi-structured, theme-based interview. The study found out that case company’s BI system was mostly used for group performance reporting. Ad-hoc and business user-driven information needs were mostly fulfilled with self-made tools and manual work. It was felt that necessary business information was not easily available. The concept of self-service BI was perceived to be helpful to meet such reporting needs. However, it was found out that the available data is often too complex for an average user to fully understand. The respondents felt that in order to self-service BI to work, the data has to be simplified and described in a way that it can be understood by the average business user. The results of the study suggest that BI programs struggle in meeting all the information needs of today’s businesses. The concept of self-service BI tries to resolve this problem by allowing users easy self-service access to necessary business information. However, business data is often complex and hard to understand. Self-serviced BI has to overcome this challenge before it can reach its potential benefits.

PRODUCT DATA MANAGEMENT FOR FINNISH SMALL AND MEDIUM-SIZED MANUFACTURING ENTERPRISES - Towards a viable information system concept

Product Data Management (PDM) systems have been utilized within companies since the 1980s. Mainly the PDM systems have been used by large companies. This thesis presents the premise that small and medium-sized companies can also benefit from utilizing the Product Data Management systems. Furthermore, the starting point for the thesis is that the existing PDM systems are either too expensive or do not properly respond to the requirements SMEs have. The aim of this study is to investigate what kinds of requirements and special features SMEs, operating in Finnish manufacturing industry, have towards Product Data Management. Additionally, the target is to create a conceptual model that could fulfill the specified requirements. The research has been carried out as a qualitative case study, in which the research data was collected from ten Finnish companies operating in manufacturing industry. The research data is formed by interviewing key personnel from the case companies. After this, the data formed from the interviews has been processed to comprise a generic set of information system requirements and the information system concept supporting it. The commercialization of the concept is studied in the thesis from the perspective of system development. The aim was to create a conceptual model, which would be economically feasible for both, a company utilizing the system and for a company developing it. For this reason, the thesis has sought ways to scale the system development effort for multiple simultaneous cases. The main methods found were to utilize platform-based thinking and a way to generalize the system requirements, or in other words abstracting the requirements of an information system. The results of the research highlight the special features Finnish manufacturing SMEs have towards PDM. The most significant of the special features is the usage of project model to manage the order-to-delivery –process. This differs significantly from the traditional concepts of Product Data Management presented in the literature. Furthermore, as a research result, this thesis presents a conceptual model of a PDM system, which would be viable for the case companies interviewed during the research. As a by-product, this research presents a synthesized model, found from the literature, to abstract information system requirements. In addition to this, the strategic importance and categorization of information systems within companies has been discussed from the perspective of information system customizations.

Characterization of design of a product for additive manufacturing

The purpose of conducting this thesis is to gather around information about additive manufacturing and to design a product to be additively manufactured. The specific manufacturing method dealt with in this thesis, is powder bed fusion of metals. Therefore when mentioning additive manufacturing in this thesis, it is referred to powder bed fusion of metals. The literature review focuses on the principle of powder bed fusion, the general process chain in additive manufacturing, design rules for additive manufacturing. Examples of success stories in additive manufacturing and reasons for selecting parts to be manufactured with additive manufacturing are also explained in literature review. This knowledge is demanded to understand the experimental part of the thesis. The experimental part of the thesis is divided into two parts. Part A concentrates on finding proper geometry for building self-supporting pipes and proper parameters for support structures of them. Part B of the experimental part concentrates on a case study of designing a product for additive manufacturing. As a result of experimental part A, the design process of self-supporting pipes, results of visual analysis and results of 3D scanning are presented. As a result of experimental part B the design process of the product is presented and compared to the original model.

Developing Supply Chain Process Management and Measurement in Global Manufacturing Company

The objective of this research is to create a current state analysis of pulp supply chain processes from production planning to deliveries to customers. A cross-functional flowchart is being used to model these processes. These models help finding key performance indicators (KPIs) which enable examinations of the supply chain efficiency. Supply chain measures in different processes reveal the changes need processes that affect the whole supply chain and its efficiency and competitiveness. Structure of pulp supply chain differs from most of the other supply chains. The fact that there are big volumes of bulk products, small product variations and supply forecasts are made for the year ahead make the difference. This factor brings different benefits but also challenges when developing supply chain. This thesis divides pulp supply chain in three different main categories: production planning, warehousing and transportation. It provides tools for estimating the functionality of supply chain as well as developing the efficiency for different functions of supply chain. By having a better understanding of supply chain processes and measurement the whole supply chain structure can be developed significantly.

Monitoring Directed Energy Deposition Processes in Additive Manufacturing

The purpose of this study is to find out how laser based Directed Energy Deposition processes can benefit from different types of monitoring. DED is a type of additive manufacturing process, where parts are manufactured in layers by using metallic powder or metallic wire. DED processes can be used to manufacture parts that are not possible to manufacture with conventional manufacturing processes, when adding new geometries to existing parts or when wanting to minimize the scrap material that would result from machining the part. The aim of this study is to find out why laser based DED-processes are monitored, how they are monitored and what devices are used for monitoring. This study has been done in the form of a literature review. During the manufacturing process, the DED-process is highly sensitive to different disturbances such as fluctuations in laser absorption, powder feed rate, temperature, humidity or the reflectivity of the melt pool. These fluctuations can cause fluctuations in the size of the melt pool or its temperature. The variations in the size of the melt pool have an effect on the thickness of individual layers, which have a direct impact on the final surface quality and dimensional accuracy of the parts. By collecting data from these fluctuations and adjusting the laser power in real-time, the size of the melt pool and its temperature can be kept within a specified range that leads to significant improvements in the manufacturing quality. The main areas of monitoring can be divided into the monitoring of the powder feed rate, the temperature of the melt pool, the height of the melt pool and the geometry of the melt pool. Monitoring the powder feed rate is important when depositing different material compositions. Monitoring the temperature of the melt pool can give information about the microstructure and mechanical properties of the part. Monitoring the height and the geometry of the melt pool is an important factor in achieving the desired dimensional accuracy of the part. By combining multiple different monitoring devices, the amount of fluctuations that can be controlled will be increased. In addition, by combining additive manufacturing with machining, the benefits of both processes could be utilized.

Improving purchasing process for small purchases at a manufacturing company in chemical industry

This thesis was conducted on assignment by a multinational chemical corporation as a case study. The purpose of this study is to find ways to improve the purchasing process for small purchases at the case company. The improvements looked after are mainly cost and time savings. Purchasing process is the process that starts from the requisition of goods or services and ends when the invoice is paid. In this thesis the purchases with value less than 1000€ are considered to be small. The theoretical framework of the thesis consists of general theoretical view of costs and performance of the purchasing process, different types of purchasing processes and a model for improving purchasing processes. The categorization to small and large purchases is the most important followed by the division between direct and indirect purchases. Also models that provide more strategic perspective for categorization were found to be useful. Auditing and managerial control are important parts of the purchasing process. When considering the transaction costs of purchasing from the costs–benefits perspective large and small purchases should not have the same processes. Purchasing cards, e-procurement and vendor managed inventory are seen as an alternative to the traditional purchasing process. The empirical data collection was done by interviewing the company employees that take part of the purchasing process in their daily work. The interviews had open-ended questions and the answers were coded and analyzed. The results consist of process description and assessment as well as suggestions for potential improvements. At the case company the basic purchasing process was similar to the traditional purchasing process that is entirely done with computers and online. For some categories there was already more sophisticated e-procurement solutions in use. To improve the current e-procurement based solutions elimination of authorization workflow and better information exchange can be seen as potential improvements for most of the case purchases. Purchasing cards and a lightweight form of vendor managed inventory can be seen as potential improvements for some categories. Implementing the changes incurs at least some cost and the benefits might be hard to measure. This thesis has revealed that the small purchases have potential for significant cost and time savings at the case company.