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HomeFinance and AccountingBusiness Payments7 Ways Data Analytics Can Boost Your Manufacturing Efficiency

7 Ways Data Analytics Can Boost Your Manufacturing Efficiency

Photo by Ivan Samkov: pexels

Data analytics has been revolutionizing a variety of industries, and manufacturing is one of them. Pecan – predictive analytics can be applied to various areas of the production and manufacturing process to analyze data holistically for added productivity and improved product quality.

As a manufacturing business trying to keep up with the current ways, you must prioritize integrating modern analytics into your operations, and here are seven ways in which it can boost your manufacturing efficiency.

1. Discrete Event Simulation

Discrete Event Simulation is a tool of data analytics that can be used to view the whole manufacturing process divided into several distinct sequences of events at discrete time points.

This helps to simplify the ever-so-complex process of manufacturing. DES can be integrated with several tasks, such as production scheduling, allocating resources, capacity planning, identifying bottlenecks, and much more to add clarity to the process.

2. Product Quality Analytics

Data analytics also finds its application in enhancing the overall product quality, which has a direct impact on how users receive the product, their experience, and the long-term of your business.

Product quality analytics helps speed up quality checks and assessments. Using this form of data analytics helps operators identify in time the quality issues pertaining to the product design so that timely actions can be taken towards resolving these issues.

3. Productivity Analytics

Productivity analytics can help you ensure that the manufacturing facility runs smoothly by leveraging data analytics. With productivity analytics, you can make predictions about potential machine downtimes, poor resource allocation, and much more.

When identified and addressed, these factors can be handled in ways that prevent them from impacting the profitability of your manufacturing enterprise. Data analytics solutions such as simulation, optimization, and demand forecasting help ensure your facility runs to its maximum capacity.

4. Throughput Optimization

While minimal downtime is essential for a manufacturing unit to manufacture an adequate number of finished goods in time, there can still be operating inefficiency that reduces manufacturing throughput despite no unplanned downtimes.

It becomes easier to identify challenges and inefficiencies that affect the throughput with the help of the available data. Data analytics allows you to make changes to the production parameters, which results in operational optimization. And the outcome of this optimization is an increase in manufacturing throughput.

5. Manufacturing Yield Optimization

The raw materials used in the manufacturing process greatly decide the quality of the yield, which is the product. This is all the more relevant for manufacturing units from the chemical, pharmaceutical, and mining industries.

With data analytics, it is possible to control the production parameters in ways that lead to the enhancement of the quality of the manufacturing yield. When you provide the system with data pertaining to the material available, it assesses the data across the facility machines and how changes in the input variable can impact the machine throughput.

6. Production Scheduling

Some of the most common conventional ways to handle production schedules are using spreadsheets and rule-based heuristics.

However, with the advent of technology, data analytics can significantly improve your production planning by making it possible for you to implement changes in the plans in real-time. This not only adds efficiency to your process but also reduces the time that it takes for you to implement the plan.

7. Predictive Maintenance

Machine downtimes from equipment failure can cost you a lot more than a repair. It might cost you replacements and the time wasted from machine downtime. With predictive maintenance, you can set periodic maintenance on your schedule based on the data analytics specific to the machines that you use.

This utilizes artificial intelligence and machine sensor data to predict the chances of a machine’s breakdown at any given point in time, thus helping you stay prepared.

When implemented in the right ways, data analytics can be your one-stop solution that uses all your business data to improve the production and sales process. There’s potential for every type of business, from chemical, biomedical, mechanical, and nuclear to industrial to get benefited from data analytics. All it takes is some professional help to help you understand the technology and how it works so that your teams can make the most out of it.

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