Management of intralogistics in manufacturing industry through data visualization : a case study

Intralogistics is part of the logistics and therefore one of the significant factors of costs structure that the companies have. Logistics is a necessity in manufacturing companies to provide the cus- tomer with their goods. The production needs materials to be able to manufacture the goods. This is provided by the logistics department. Also, the finished goods need logistics to be able to reach the customers. This is why logistics is one of the main areas in the manufacturing company. Intralogistics is the part of the logistics chain that includes logistics partners and manufacturing site. This means that the scope is wider than in the warehouse management. Therefore, intralo- gistics has a major part in the whole logistics operation, and it should be optimized. This research aims to provide information on how data visualization can be implemented in the manufacturing industry and what are the benefits of this implementation. To reach this aim the theory research in the chapter 2 included theory of data analytics, materials management, logis- tics and intralogistics data visualization. In chapter 3 the empirical research was concluded as a case study and the case study framework was followed. The empirical research included inter- view research which was presented in the current state analysis. The case company has noted problems in intralogistics due lack of visibility that this thesis aims to increase. The case company and the current state of it were presented. The case company and the benchmark research em- phasize the need for visualization on the warehouse related reporting. The need for reporting was mentioned in the context of determining the bottle necks and optimizing the resources. The sources for this research were collected in the literature review, interviews and data collection from the case company’s ERP system. Based on theoretical and empirical study, the result op- tions were presented. The empirical research also evaluated the impact of the options presented. As a result of this research, the plan with two phases was formed. This plan included two phases of implementation. Phase one is the predictive dashboard including tables and graphs. Phase two is an interactive and targeted perspective dashboard including tables, graphs and maps. The solution was planned to be executed in phases to ensure fast implementation together with the most beneficial results. Even though the results were conducted based on the case company’s description and current state analysis, the results may be used in other companies and industries because theoretical research was conducted from the general point of view. The evaluation of the impacts indicated that the phase 2 would have major impact in the intralogistics. For the recommendation for future research other visualizations, artificial intelligence and machine learning may be relevant.