BI,Case Study
OPTIMIZE MANUFACTURING QUALITY WITH KEY PERFORMANCE INDICATORS
INTRODUCTION A leading manufacturer in Germany wanted to visualize and analyze their manufacturing quality across all plants for quality monitoring to discover improvement opportunities in a data-driven way. CASE DESCRIPTION The client needed a monitoring solution of their manufacturing processes across all plants. The ob- jective was to conduct monitoring and discover the root cause of production issues. The current reporting solution was provided by an external team and not sufficient for multiple reasons: ● New features (usually new KPIs) took too much time to be deployed as the development of the solution was not under their control ● The analysis-flexibility was limited as the users had no possibility to implement some new busi- ness logics by themselves and raw data was not accessible for further self-analysis ● The response time was too high as the aggregated KPIs were not pre-calculated To fulfill all the business requirements, the required data needed to be integrated by business terms, business rules had to be applied, performance needed to be optimized and the results must be pro- vided in a user-friendly way with flexibility for further self-service analysis. Furthermore, data sci- entists needed to be able to access the data in its raw format.
Figure 1: Inflexible and indolent reporting solution
The solution was a multi-layer data warehouse architecture to integrate all necessary data from multiple sources to provide business value in an agile fashion.
Data Vault 2.0 was the methodology used to create the Business Intelligence solution in a scalable, agile and future-proof way. After the integration of the data into the Raw Data Vault, the data was transformed into information by applying business rules. The results were provided in a dedicated information delivery layer of the data warehouse architecture. For most business rules, the data was already aggregated to ensure performance when reading the results by the front-end tools. The KPIs could be used by any business analytics tool the business users, business analysts as well as data scientists are comfortable using.
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Optimize Manufacturing Quality With Key Performance Indicators © Scalefree International GmbH 202 3
Figure 2: Scalable Business Intelligence Solution
The developed solution consisted of an integrated data warehouse where all raw data was available as it can be found in the source system. From there, data scientists could use this raw data for their analysis purposes. Requested KPIs were pre-calculated to provide a single version of the truth and to ensure fast results on demand. Business Users and Analysts are now versed in doing further self-ser- vice analysis with tools they are familiar using. All data was integrated by business terms for better understanding and the access to the Information Marts didn’t burden the source systems any longer. Furthermore, the solution is now maintained by an internal team which makes feature integrations much easier and faster, especially due to the flexible Data Vault modeling approach.
Scalefree International GmbH Schützenallee 3, 30519 Hannover, Germany
P: +49 (511) 879 893 41 M:+49 (175) 811 0336 F: +49 (511) 879 893 49
info@scalefree.com www.scalefree.com
CEOs: Michael Olschimke & Christof Wenzeritt
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Optimize Manufacturing Quality With Key Performance Indicators © Scalefree International GmbH 202 3
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