The design process is surprisingly similar for many projects, from software design to large manufacturing. It's how you apply different aspects of the design process that can help make your product unique and of good quality. Here are six aspects of the design process you can apply to large manufacturing.
When you first begin a manufacturing project, your team should generate as many ideas as possible. Some of these may be too grand or may not work, but the creativity is what's important here. The more creative you are in the brainstorming stage, the better your designs and product will be. You can work as one group, asking what-if questions and practicing visual mapping. Or you can break into smaller groups and try speedstorming, a process where each group tries to come up with a certain number of ideas in a certain small increment of time and then you come back together to discuss these ideas. Your brainstorming ideas don't have to work; they just need to generate creative problem solving and push people toward making connections they otherwise might not.
Generative design is a relatively new aspect of the design process. To perform this type of design, you need to input your brainstorming ideas and project goals into generative design software, which can analyze various design strategies and implementations, test them and learn from them much more quickly than employees can do in analogue processes. This frees up your team members' time to think of designs to create and interact more with customers. Generative design is particularly good for manufacturing because so many processes go into designing things like cars and aircrafts.
A good design process requires a solid product vision and implementation strategy. You should start with three questions. What is your problem? Who are you solving the problem for? What outcome do you need to happen? Use these questions to form a set of goals to guide the design team. Remember to adjust your strategy as you move through the process. Check whether your solutions are working, whether your product is functional so far and if it's meeting the needs of your audience. If it is, keep going. If not, take a step back and reassess. For example, if you need to install industrial piping Utah, you'll need to assess your needs, put together a solid design and have a plan mapped out for installation. This is so you can collaborate with the installation team more easily and efficiently and be able to make adjustments as you go.
Predictive maintenance refers to implementing AI and machine learning in manufacturing so certain devices can report their conditions in real-time. This is common in modern cars. Most cars these days incorporate computer systems that keep track of oil levels, filter integrity and many other maintenance aspects of cars. These systems are programmed to notify the car's owner when they need maintenance or service so the owner doesn't need to check manually. Systems like these in other industries can even be capable of resolving problems themselves, such as AI capable of fixing damaged code in software. Predictive maintenance saves both the user and manufacturer of a product time, resources and cost.
The final step of any design process must include testing. Even if you follow your strategy to the letter, there can be unexpected issues. Maybe there are errors in a line of code somewhere or maybe some wiring is loose in your large manufacturing project. Testing is the final stage of the design process where you seek out bugs and errors so you can correct them before making your product available on the market. You can do in-house testing for functionality and incorporate user testing to make sure the product appeals to your audience and is easy to use.
It's important to apply steps like these to any design process so your team can be creative, understand the needs and limits of the product and test it before releasing it.