Manufacturing Data Analytics: The Next Big Thing

Bhagyashri Kambale | March 22, 2022 | 389 views
MANUFACTURING
Manufacturing analytics, or real-time manufacturing analytics, is the process of collecting, cleansing, and analyzing data from machines to forecast their future use, prevent failures, forecast maintenance requirements, and identify areas for improvement.

“The goal is to turn the data into information and information into insight.”

- Carly Fiorina, ex CEO of Hewlett-Packard

Manufacturing data incorporates all structured and unstructured information collected manually or through software from machines and humans throughout the manufacturing process, up to the point at which a product is launched to the market.

In this article, we will look at the use cases of data analysis in manufacturing and some of the start-ups from the U.S. that are helping manufacturers gather their real-time manufacturing analytics.


Data Analysis in Manufacturing: Use Case Analytics


Demand Forecasting

Forecasting demand is highly dependent on historical data on supply levels, material costs, purchase trends, and customer behavior. Manufacturers can use analytics to accomplish the following:
  • Define the products to be manufactured in a time frame
  • Define products that are no longer in stock
  • Determine the quantity of products to be manufactured
  • Forecast sales prospects


Inventory Management

Forecasting demand enables manufacturers to manage inventory, purchase materials, and optimize storage capacity based on data. Additionally, manufacturing industry data analysis provides insight into:
  • The sales-to-inventory ratio indicates the average inventory value over net sales.
  • Days in inventory refers to the time a manufacturer retains before selling a product.
  • Gross margin return on inventory (GMROI) is a term that refers to the amount of gross margin a manufacturer receives for each dollar invested in inventory.


Maintenance Optimization

Data collected from various manufacturing machines, tools, and devices, as well as information about operations and the gears required for the machines, can be analyzed to:
  • Predict when a machine will require maintenance based on the amount of time and the operations in which it has been used.
  • Identify and resolve operational anomalies caused by or will result in machine failure.
  • Prevent downtime by scheduling machine breakdowns, repairs, and replacements in advance.


Price Optimization

Utilizing analytics can assist manufacturers in determining the actual cost of a product based on the costs of materials, labor, machines, and tools used or purchased during the manufacturing process. Additionally, manufacturers can optimize prices based on data about competitors, market trends, consumer behavior, and purchase history. Additionally, analytics can assist in setting dynamic prices that are determined by demand, supply, competition, and subsidiary product prices.


Analytics for Manufacturing as a Service: Three U.S.-based Startups


Uptake

Uptake offers predictive analytics solutions powered by artificial intelligence for various industries. It provides a compass, which allows organizations to optimize work orders and scout. This allows users to analyze data and custom alerts and radar to get failure and anomaly detection solutions. Failure prediction, noise filtering, situational analytics, and detecting changes in operational behavior are just a few of the features that these systems offer to their customers today. The product, by Uptake, is intended for use in various industries like mining, construction, fleet management, manufacturing, aviation, government, and oil and gas.


Seeq

Seeq is a leading provider of industrial data analytics solutions. Its big data analysis solutions help in the analysis and comprehension of industrial process data (IPD) more effectively and quickly than typical alternatives. Reduced analysis time, quicker relationship discovery, ERP and other system connectivity, support for business intelligence (BI) tools such as Excel, Tableau, SAS, and MATLAB, and collaboration support are some of the features.


Sight Machine

Sight Machine provides a platform for manufacturing applications that utilize digital twins. It provides solutions for continually analyzing images captured by industrial cameras, sensor data, and data from manufacturing systems to improve product quality and operations. It provides real-time visibility and actionable data for every part, machine, line, and plant manufacturing process. Its clientele includes Nike, Sony, Nissan, and Google, to name a few.


Final Word

Big data analytics in manufacturing assists businesses in identifying the parameters that have a direct effect on production. Additionally, modifying the target process helped businesses increase productivity by 50%.

McKinsey estimates that when analytics are used in design-to-value workflows and projects, manufacturers' gross margins can increase by as much as 40%. Manufacturing analytics can help with design-to-value, supply chain management, and after-sales support. Real-time manufacturing analytics enables manufacturers to optimize their overall production. 


FAQ


Why is data critical in manufacturing?

Big data helps manufacturers understand their customers' needs and wants better. To launch a new product or upgrade an old one, data is required to make it appealing to customers and assess the risks of competition.


What is production analysis?

Production analysis visualizes production output and helps assess production losses and associated costs.


What is predictive manufacturing?

Predictive manufacturing uses descriptive analytics and data visualization to provide a real-time perspective of asset health and reliability performance.

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