Production Analytics: Helping Manufacturing Business Improve Productivity
Data, cloud, action, analytics, IoT, are buzzwords we so often hear nowadays with manufacturing companies scaling higher and slowly turning to smart manufacturing and implementation of the Internet of things. Many companies have adopted smart manufacturing and competition hence has taken a different face each business organization focusing on achieving positive results and desired outcomes. Now this deep level of data manipulation for excellent manufacturing is possible via Production analytics and leveraging production analytics in manufacturing has become a necessity.
How is Production analytics beneficial? It increases quality production, reduces operation flaws, increases efficiency and saves money and time. Production analytics could be effectively used for the following functions:
- Enhancing productivity
- Improve Product profitability
- Enhance supply chain management leading to improved delivery time
- Increase energy efficiency
- Efficient and informed planning for material needs
Production Analytics are quantitative metrics associated with content development. It consists of the number of assets the company produces in a given time frame, the speed of producing the assets and the ratio of content produced for specific sales stages and consumer’s character. To simply put it is extracting valuable insights from your data through visualization. Your production data aggregated in a balanced content program will give results to help solve business problems to improvise your production process and generate higher profits and stay competitive throughout. And that is how data analytics are helping companies up their game in the manufacturing business.
Now one must also remember that making informed decisions concerning one’s manufacturing processes is directly related to quality and depth of information one has at hand. One must understand what information is relevant and what actions are required for the outcome. While making use of production analytics one must narrow down their query to specific business challenges to which information as actionable insights can be drawn from the patterns and examples. Just by possessing a large amount of data at hand for analysis does not entail that one can extract desirable and insights needed.
With manufacturing analytics services, thus Production in manufacturing companies has higher yields and efficient operations with enhanced uptime utilization, increased throughput and reducing downtime through better diagnostics. The feature of predictive analysis that comes with manufacturing analytics helps manufacturers detect their customer’s behavior and preference thus optimizing the preferred products in the future.
How to get access to production analytics? There are multiple platforms that provide data visualization and data analytics tools coming to the rescue of manufacturing business.
Visualr is rightly known for its manufacturing analytics services. Users get access to real time production data and with the real time factory floor analytics manufacturing companies can have optimized performance and productivity. Visualr has multiple data sources connectivity which is a plus point for data visualization. With Visualr, Manufacturing businesses have the potential to optimize their productivity as users get to see comparative display of production lines, their efficiency, and number of defects increasing or trends developing. With this producers can further make informed and fact-based decisions.
Meeting the need of the customer is what every manufacturing business thrives to perform and with higher demand comes higher profits. Visualr with its Data Visualization tools facilitates companies with visualized quality of individual products in the production process which further necessitate optimizing such products and meeting the needs of the customer which enhance the supply chain mechanism. Defects in the production operation are also detected with analytics and this helps in remediating the recurring defects.Share on Facebook Share on Twitter Share on Pinterest