The manufacturing space is one that’s rife with opportunities for innovation. As a sector that needs to be efficient in order to truly be cost effective, finding ways to make things run better, faster, and with a more informed approach is a big priority for manufacturers.
Today, with the various technologies we have available to us — from artificial intelligence to robust data analytics platforms and the internet of things (IoT) — the manufacturing space is ready for optimization. But what exactly does that look like? That’s what we’d like to address today.
In this article, we’re taking a close look at the manufacturing process — from sourcing to distribution — and looking at how technology can enhance each step of the journey.
Vendor management is about more than just building relationships with your suppliers. As a customer, you actually have the opportunity to help your vendors be more proactive in how they provide their products to you. For instance, if you have a system that’s consistently checking your inventory and proactively letting suppliers know when you will need a new order, they will have the time to prepare it and supply it before you run out. This means that you can avoid stalling your operations due to a shortage of raw materials.
The great thing here is that you don’t need to spend time building these algorithms. There are a number of existing options available that you can plug into your systems and benefit from almost immediately.
Technology can also play a role in quality management. By assessing and testing the quality of each component of your product on a consistent basis — and gathering and analysing that data — you can give informed feedback to your vendors so that they can improve their input. This approach to optimisation will not only improve your vendor relationship, it will also reduce the potential loss of income resulting from a subpar product.
One of the primary advancements we’re seeing on the shop floor is automated data collection. Having visibility into what’s taking place — like work orders, sales orders, items in production — and what still needs to happen can make it much easier to make informed decisions throughout the manufacturing process.
Another innovation in the production process is remote process automation (RPA). With this approach, anything that’s a repetitive, manual task is automated, freeing your people up to do more important and strategic tasks. As you implement this technology, however, you and your team will be responsible for “educating” the system around what to do in each scenario that might present itself.
Waste management is another important area to consider, as it poses a high risk from a cost perspective. If manufacturers aren’t minimising their waste, their processes are bound to be highly inefficient — and expensive.
Once a product is manufactured, it’s time to send it down the road to the end-user. Here, whether they’re working with a partner or managing distribution themselves, there’s a big opportunity to optimise costs with the right technology solution. Data rich platforms can drastically improve transportation management by categorizing customers by region, creating optimal routes and driver schedules, and enabling tracking systems that provide real-time visibility to customers.
While a number of manufacturers currently supply their customers through third-party distributors, some others have transitioned to selling their products directly to end-users. There’s value in this approach from a data collection perspective. With customer information such as purchasing behaviour in hand, manufacturers can better plan their output requirements into the future. Here, the data that’s sourced from each and every production process can help you understand where waste could be reduced — and guide you to uncover more efficient methods for doing the same thing.
In a complex manufacturing process, even the shortest downtime can be costly. This is where it can pay to be proactive, using data from across the manufacturing process to carefully plan an outage at the least disruptive time. To get this right, you need data collection points within each component of the process, giving you the full picture of the systems and machines at play.
You can also use data and machine learning for proactive maintenance. With the right information around a machine, how long it’s been used, and where it might be having some issues, your system could prompt your maintenance team or provider to schedule a tune-up. The system could also tell you the tools required for conducting the maintenance, and flag any areas that might need particular attention.
Looking ahead at where manufacturing is going, there are a number of significant changes on the horizon. For one, we may be looking at an industry that will be fully digital in just a matter of years. This may be hard to believe given that manufacturing has been such a predominantly in-person function, but the COVID-19 pandemic uncovered just how feasible it is to make a shift to remote-first and digital-first manufacturing. Now, it’s up to the industry to show us what that looks like in practice.
The other major transition we’re likely to see is that decision making will stop being human dependent. Instead, it will be driven by algorithms generated with robust machine learning platforms. The dependency on humans will remain on building the appropriate models based on the manufacturing operation at hand.
At InTWO, we’re excited to see where the industry goes next, and are looking forward to partnering with our customers to bring these changes to life.
For more information on how InTWO partners with manufactures to help them optimise their operations, get in touch.