New knowledge and insights are generated when big data is collected and processed. Traditionally, business generated data internally from operations and transactions across the value chain such as sales, customer service visits, orders, interaction with supplier as well as data gathered from research, surveys or other sources externally. Today, with improved software and connectivity, the products become smarter which makes it easier to collect and generate large amount of real-time data. The fast growing volumes and varieties of big data bring many challenges for companies on how to store, manage, utilize and create value from these data. This thesis represents a case study of a large heat pump manufacturer, Bosch Thermoteknik AB, situated in Tranås, Sweden. Bosch Thermoteknik AB has started to collect data in real time from several heat pumps connected to the internet. These data are currently used during development phase of the products and occasionally to support installers during maintenance services. The company understands the potential benefits resulting from big data and would like to further deepen their knowledge on how to utilize big data to create value. One of the company’s goals is to identify how big data can reduce maintenance costs and improve maintenance approaches. The purpose of this study is to provide knowledge on how to obtain insights and create value by collecting and analyzing big data from smart connected products. A focus point will be on improving maintenance approaches and reducing maintenance costs. This study shows that if companies create capabilities to perform data analytics, insights obtained from big data analytics could be used to create business value targeting many areas such as: customer experience, product and service innovation, organization performance improvement as well as improving business image and reputation. Creating capabilities requires deploying many resources other than big data, including a technology infrastructure, integrating and storing a vast amount of data, implementing data-driven culture and having talented employees with business, technical and analytics knowledge and skills. Insights obtained through analytics of big data could provide a better understanding of problems, identifying the root causes and reacting faster to problems. Additionally, failures could be prevented and predicted in the future. This could result in the overall improvement of maintenance approaches, products and services.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-162291 |
| Date | January 2019 |
| Creators | Kokoneshi, Renisa |
| Publisher | Linköpings universitet, Energisystem |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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