How Data Can Improve Manufacturing Operations
Manufacturing is on the brink of a data-driven revolution. New technologies such as industrial IoT are at the vanguard of this rapid progression. Remote sensors mounted on factory equipment, warehouse assets, and even factory workers transmit large amounts of invaluable manufacturing data that can be used to improve productivity, profitability, and safety. Let’s explore how data is transforming manufacturing operations and look at a few use cases of manufacturing data in action.
The Value of Data for Manufacturing Operations
The invention of the assembly line revolutionized the manufacturing field nearly a century ago. Today, smart manufacturing is just as transformative, reshaping nearly every aspect of the manufacturing process. This transformation, sometimes referred to as Industry 4.0, is characterized by increased connectivity, reliance on data, and smart automation. Here are seven ways that manufacturing operations managers are harnessing data to improve their products and processes.
Gain a deeper understanding of consumers’ current product preferences
Gathering data from a variety of sources, manufacturers can gain insights into how consumers in various markets interact with their products and the value they place on current and future functionalities. This knowledge makes it possible to mitigate much of the risk that comes with developing new products or redesigning existing ones.
Forecast future demand with greater accuracy
Manufacturers face a Goldilocks conundrum: how to produce just the right amount of product to support current consumer demand. Too little creates shortages, while too much results in unnecessary price discounting. Data can be used to track historical demand, emerging consumer trends, weather events, and more to help manufacturers sync production schedules with demand.
Data streamed from a network of sensors mounted on machinery, warehouse, and human assets can help decision-makers spot opportunities for increasing production. With advanced data analysis and modeling, manufacturers can boost profitability by identifying which parts of the production process are ripe for optimization.
Enhance quality control
Quality control issues create unhappy customers and sap profitability. Manufacturers can analyze warranty claims and production line data to identify patterns that point to a specific design flaw or manufacturing defect.
Improve worker safety
Manufacturing analytics can improve the safety of front-line manufacturing, warehouse, and transportation workers. Wearable sensors can track the temperature, air quality, noise levels, and other stressors workers are routinely exposed to, alerting supervisors to the need for intervention. IoT sensors can detect when worker posture deviates from expected norms, indicating an issue such as a fall or failure to adhere to correct ergonomic positioning.
Keeping fragile supply chains intact has become an increasingly difficult challenge. But predictive analytics programs can alert manufacturers about impending disruptions before they happen. Using data from transportation partners and third-party sources, analytics programs can accurately forecast disruptions due to weather, political unrest, vendor insolvency, or transportation bottlenecks.
Manufacturing Operations Data Use Cases
Here are three ways that harnessing the power of data can improve profitability, processes, and customer experience.
With real-time data generated by equipment and machinery, manufacturers can predict the likelihood of a failure and when it’s most likely to occur. With this information, technicians can ensure they have the necessary parts on hand and conduct repairs at the optimal time. Preventative maintenance reduces downtime and increases productivity.
Mitigating supply chain risks
As supply chains grow increasingly fragile, the ability to anticipate and react to potential disruptions has become critically important. Using data gathered internally from vendors and from third-party data sources, data analytics tools can flag shipments facing delays, spot emerging issues with parts and raw material contractors, and anticipate demand that will require increased production capacity to meet. Decision-makers who know about impending issues before they occur have the lead time to react accordingly to avoid serious operational disruptions.
New product development
Manufacturing data can be used to create a digital twin that uses data to replicate real-world conditions that accurately predict product performance, often without the production of an extensive series of physical prototypes. This can significantly reduce R&D costs and result in accelerated time to market for new products.
Snowflake for Manufacturing Operations
For more manufacturers, using data to modernize operations is becoming standard practice. But many companies still rely on on-premises infrastructure or fragmented storage solutions that struggle to keep pace with the processing and storage demands of the data generated by manufacturing operations. With near-unlimited storage and compute power, Snowflake enables manufacturers to aggregate large amounts of data in a variety of formats and quickly access and analyze data without worrying about integration and interoperability issues that hobble data analysis efforts.
With Snowflake, manufacturers can use real-time data gathered from networks of interconnected IoT devices to gain valuable insight into throughput and critical processes. Snowflake allows manufacturers to power IoT innovation with sensor and device data analysis, increase supply chain efficiency, and improve the quality and speed of production. Additionally, manufacturers can take advantage of the Snowflake Marketplace for access to live third-party data to supplement proprietary data.
See Snowflake’s capabilities for yourself. To give it a test drive, sign up for a free trial.