Make manufacturing more competitive
Embracing digital transformation is a winning trump card for successful manufacturing companies. However, many businesses find it difficult to identify and deploy a winning digital strategy.
Rulex’s complete range of tried and tested solutions can orchestrate your manufacturing chain, making digital transformation a smooth process.
Our no-code unified platform transforms manufacturing data into improved productivity, minimized costs, and seamless overall management.
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Why manifacturers choose Rulex
Improve operation productivity
We help manufacturing companies put their big data to work by generating advanced analytics that increase plant performance. With Rulex, manufacturing operators can streamline process operations, improving productivity and profitability.
Cut risks and costs
Our algorithms can detect anomalies across the production chain and propose fast preventative actions, which solve issues before they have an impact, preventing financial loss for the business. Rulex helps operators prevent machine failure, and the production of defective items, reducing the risk of production standstills and the wasting of raw materials.
By automatically monitoring every step in the manufacturing process, Rulex supports management while ensuring the correct functioning of the plant. Our no-code software and user-friendly interface allow manufacturing operators to manage data-driven insights with confidence, keeping every step under control.
What we do for manufacturing
Our tried and tested solutions can help you face current and future challenges, and keep up with global competition.
Master data correction
High quality master data is an essential foundation for any successful business operation. We offer a complete suite of solutions to manage data quality, from Rulex RDC (a tool for generating automated business rules and correcting data inconsistency) to data cleansing and deduplication tools. We are able to eliminate data errors by up to 100%.
Selling malfunctioning products can result in financial loss and cause serious damage to the reputation of a company. Predictive quality identifies these suboptimal products before they create problems. Rulex collects production data and performs AI analysis to identify potential production issues or product combinations, which may result in a high percentage of defective items. The benefits include increased customer satisfaction, reduction in costs incurred during pre-sales (avoiding rework, waste of material) and post-sales (fewer claims, repairs, servicing, and returns).
The shutdown of plants due to failures is one of the most serious problems for the manufacturing industry. Predictive maintenance, thanks to machine learning and eXplainable AI, can prevent shutdown by identifying potential malfunctions. Rulex collects production flow data, saving them on an MES system. Data are then analysed and processed through our advanced AI algorithms, which detect anomalies, test correlations, and propose actionable responses to issues that may arise. This prevents major failures that may lead to process standstills, resulting in disruption of production lifecycles. Effective predictive maintenance reduces costs by identifying malfunctions in a single component, which allows operators to repair the single isolated component, and preventing other parts from breaking. There is also an essential positive impact on workplace safety levels.
Getting stock levels right by correctly predicting demand is a huge challenge for every manufacturer; over- and under-stocks are operational and financial headaches. We identify patterns in historical data to accurately forecast future demand. Our solution is transparent, thanks to its eXplainable AI core, versatile, as it can be applied to different market scenarios, and extremely precise, improving prediction accuracy by several percentage points.
Any structures, such as factories and aqueducts, are complex systems, which constantly produce and consume energy and heat. Energy consumption and production can be optimized through a combination of predictive models and data-driven optimization. In a real-life scenario, where Rulex was used in the maintenance of a large aqueduct in Northern Italy, energy savings of 4% were achieved.
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