Digital Trends Changing Manufacturing As We Know It

Everyone working at any level of manufacturing shares one common fear — outsourcing. Many companies have already taken their operations overseas for cheaper labor but for the companies who are committed to staying in the U.S., finding ways to become leaner and more profitable are critical.

Manufacturing companies can waste precious time trying to find areas to maximize their profits, but the quickest way to modernize their operations for cost-cutting purposes is the use of manufacturing analytics.

Here are few ways companies can use analytics for manufacturing to improve their operations:

Self-Diagnostic Systems

When complex, heavy-duty machinery or elaborate software breaks down, it usually takes as much time to figure out what went wrong as it does to get the machine back up and running. Technology is advancing to the point where most equipment and software can self-diagnose any issues that occur. Self-diagnostic equipment saves the maintenance department the pain of trying to figure out what the issue is but more importantly, it saves troubleshooting and repair time that can be allocated elsewhere.

In the case of manufacturers selling machinery to customers, these self-diagnostic systems allow for remote diagnostics to assess a problem without sending a technician to figure out what went wrong. In some cases, the issue can be fixed by walking the customer through a step-by-step repair process or may even be repaired remotely.  

Operational Equipment Effectiveness

Getting the most out of your machinery is an important step towards maximizing efficiency, which will lead higher production levels. According to Automation World, operational equipment effectiveness (OEE) is the relation between what theoretically could be produced at the end of a process and what actually came out or was produced at the end of the process. If machinery is not producing up to its maximum efficiency, then organizations are missing out on production that could lead to higher sales and revenue numbers. A small oversight like this is why analytics for manufacturing are becoming such an integral part of more companies’ every day.

Other factors that could limit OEE include labor, energy, and materials. Companies need to continually analyze their OEE to see if they are limiting their own efficiency. A small increase in any of the three factors listed above could easily improve efficiency and production levels.

Inventory Management

It sounds better to always have too much instead of too little. But, wouldn’t be being spot-on be the best-case scenario? Analyzing inventory levels over a certain period of time can help forecast the need to order or produce more product to cover the expected sales in the same time frame. Another piece of data to consider a company’s inventory turnover ratio. The ITR is a ratio showing how many times a company’s inventory is sold and replaced over a period of time. The number of days in the time period can then be used to calculate the time it takes to sell the inventory on hand. Using ITR in replenishment or production schedules can ensure that it is never too little or too much sitting on the shelves.

Process Standardization

Most companies probably have some form of standardization in place for their manufacturing process, but is it the best process? There can still be a waste of time, money and materials in a standardized process, which is why organizations need to analyze their current processes to see what can be more resourceful and efficient. Altering the standard process can lead to cost and time savings, which will lead to more profit on a per-piece basis because the product is now a little cheaper to produce. On top of possible savings, process standardization becomes more reliable with fewer variables to worry about.

There are plenty of areas a manufacturer could use analytics to become more cost-effective and efficient, but implementing self-diagnostic systems, optimizing your OEE, improving inventory management and refining your process standardization can all lead to additional time, production and profit. Use the data available to you to make sure you’re not wasting resources that could be used elsewhere!