Technology Category
- Analytics & Modeling - Machine Learning
- Sensors - Level Sensors
Applicable Industries
- Education
- Equipment & Machinery
Applicable Functions
- Product Research & Development
- Quality Assurance
Use Cases
- Onsite Human Safety Management
- Time Sensitive Networking
Services
- Data Science Services
- Training
About The Customer
Roquette is a global leader in innovative plant-based ingredients. The company addresses current and future societal challenges by unlocking the potential of nature across the food, nutrition, and health markets. Their ingredients respond to essential needs, enable healthier lifestyles, and are critical components in life-saving medicines. The company's approach to innovation extends inwardly, and in 2018, they embarked on a digital transformation project to revolutionize their production facilities and processes. Roquette operates 25 production sites and has 250 production processes emitting between 500 and 3000 records every 30 seconds.
The Challenge
Roquette, a global leader in innovative plant-based ingredients, embarked on a digital transformation project in 2018 to revolutionize their production facilities and processes. The company faced the challenge of managing and processing large datasets from 250 production processes that emitted between 500 and 3000 records every 30 seconds. The manual processing of data was time-consuming and inefficient, hindering strategic decision-making. For instance, one team was spending 100 hours manually exporting 3000 Excel databases. Furthermore, the company's 25 production sites needed to consistently operate at the highest level, requiring the assessment of the Sigma Level, a statistical term used in manufacturing to measure how much a process varies from perfection. This task was time-consuming, requiring approximately one working week of data consolidation for each plant.
The Solution
Roquette implemented Alteryx, a data processing and analysis tool, to consolidate, process, and analyze disparate data sources. This enabled strategic decision-making at scale and significantly reduced the time spent on manual data processing. For instance, the process of exporting 3000 Excel databases was automated using Alteryx, reducing the time required from 100 hours to just three minutes. Alteryx was also used to automate the task of assessing the Sigma Level of each plant, reducing the time required from one week to less than three minutes for all plants. The tool's machine learning capabilities were used to uncover vital insights, such as the influence of external temperature on a manufacturing process. Alteryx was also used to democratize data analytics within the company, allowing employees of all analytical and coding abilities to apply analytical methods.
Operational Impact
Quantitative Benefit
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