The first step to any problem-solving method is always the collection of data. “Big data” is a design principle that takes this idea to a new priority level. Big data is changing how manufacturers use their machines by providing them with a wealth of previously unheard-of information. There’s no limit to what a manufacturer can accomplish with access to detailed reports about each floor device’s timing, function, and efficiency.
Big data isn’t the only area wherein the manufacturing sector is seeing a tech overhaul. Future-forward technologies like SUSE tools are also making a splash by providing the solutions needed to manage these substantial data reserves and revolutionize production efficiency and customization.
Manufacturing is the business of making things, and big data is the latest tool in each plant’s belt. Here are seven ways big data is making a significant impact on the manufacturing sector.
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Further integration of the IoT
The Internet of Things (IoT) is a concept in data technology referring to the collection of physical objects that can interact with the Internet as part of their function. For example, sensors are one of the main object classes that collect data. Data from these sensors or other objects transmits to other Internet-enabled devices.
This capability allows physical objects to interact with each other and carry out functions without requiring manual input. It’s an essential facet of automation and its modern development. Rather than a human and a clipboard, vital operations data now transmits automatically through the machines themselves.
A more robust, more powerful Industrial Internet of Things (IIoT) is on the horizon, with advances in manufacturing leading the charge.
Developing New Insights
Data has shown that the insights offered by big data are novel and precise. Allowing sensors and data collection points to talk to each other across the manufacturing process makes any inefficiencies or breakdowns more transparent. In essence, these technologies act as a fly on the wall inside workers’ devices.
The implementation of big data in manufacturing has a few apparent applications, namely machine maintenance and diagnostics, but industry professionals are still exploring the limits of its functionalities.
In the meantime, professionals have wasted no time collecting data from as many input and output sources as possible to leverage the power of information fully.
Predicting Maintenance Before a Shutdown
One of the worst things that can happen to a large manufacturing plant is an unplanned shutdown. These shutdowns cause revenue loss, supply chain disruption, and dissatisfied clients. Plants typically have maintenance schedules and preventive routines to keep these nasty surprises to a minimum. However, manufacturing isn’t an exact science, and no industry is immune to the unexpected.
This vulnerability is where big data can help. The maintenance team can keep the gears running by applying big data principles and tools to equipment maintenance, sensors, and analytical software.
Warnings can flag in the system by comparing component age and conditions to those matching historical data. These warnings can prevent a shutdown by allowing the maintenance team to patch a problem before it becomes a plant-wide issue. In other words, big data makes manufacturing plants more resilient against stopgaps and downtime.
Increased Supply Chain Awareness
Some of the inefficiencies in manufacturing exist in the supply chain. Excess inventory and a lack of communication surrounding supply chain conditions make it hard to predict the required materials for orders in queue. Spoiled raw materials from a lack of orders make for an expensive waste of time, effort, and revenue.
However, big data can sync the various points of a supply chain together seamlessly. This transparency would make it easier for suppliers and customers to request and schedule orders based on market conditions and needs.
The IIoT would allow professionals to automate this process, reducing the workload for staff who manage the supply chain. Inventory tracking software can place orders for materials and process client orders. Industry leaders could expect to see a massive reduction in overhead with these technologies pitching in on the heavy lifting.
Improvements in Quality Management
Another threat to revenue for manufacturers is quality management. The accidental creation of ineffective or inefficient products can result in time and money lost to repair the problem after the fact. With manual tracking and maintenance reviews, these troubles are all but inevitable.
Big data can track when these issues start to arise with the use of sensors. These sensors would monitor the component condition and product quality without taking up valuable human hours.
With these tools, problems could be flagged before the product leaves the production plant. Real-time data can reveal when a problem started, and workers can determine a solution before clients are ever aware of a problem.
Feasible Product Customization
Given the capital and effort it takes to establish a manufacturing business, it makes sense that owners and sales teams would focus on landing large orders or contracts. These high-ticket clients ensure that the production facility has the revenue it needs to keep the lights on and the gears turning. In these large contracts, customizable products tend to be left to the smaller, niche markets as a result.
By monitoring market conditions with big data, a factory sales team would be able to track orders and requests from the broader supply chain as a whole. This monitoring ability would allow the team to see when a particular product turns from niche to famous. Now, without any outside help, the business can pivot towards a new venture without missing out on their bread and butter contracts.
Increased Understanding of Asset and Production Performance
Finally, internal reviews and audits are essential for ensuring that the business is profitable and sustainable. Without feedback from customers and the marketplace as a whole, manufacturing companies have no way of knowing if the products they produce are being well-received by the world.
Utilizing big data, customer feedback on products and services becomes an automatic process. Reviews and complaints can be digitally gathered and tabulated, giving the plant’s leadership a clear indication of how the market views its products.
With these insights, the leadership team can then develop solutions for problems, addressing the customers’ needs directly without any direct input from the market itself.
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Before You Go
Big data can be the difference between preempting a problem and following behind a problem. In the world of large-scale manufacturing, trying to catch up with problems is a surefire way to lose revenue and customer faith at the same time.
