Production & Plant maintenance
Production & Maintenance is an area of major focus for osapiens. Many of our customers have global production networks. They want to optimize productions plants and harmonize the interaction of those. Another vital component is a globally synchronized capacity planning. These are the questions that our customers like to ask:
Our factory is highly automated and for this reason we need highly specialised maintenance teams to ensure our machinery is always up-and-running. However, to find the right persons with the right skills is a huge problem. How can technology help us solve this skills-shortage problem?
Well the good news is that today B2C technologies like skype or iface are allowing much better remote team collaboration. This means that highly skilled technicians can seat inside a control room, assisting a handful of more junior technicians doing the job on the ground. Throught remote redlining, wearables or remote control technologies this is now more convenient and efficient than evet. And all you need to make it work is a good internet connection inside your sites.
Often we have to realize that our production volumes are disconnected from our customers' demand. We mostly produce based on last years' experience or reactively when many customer orders come in at the same time. Is there a smart way to use our past production data or present market data to predict what volumes we shall produce?
Definitely, there are smart ways for doing so. We support many of our customers in utilizing their data to gain insight for both their production and maintenance. Our solutions enable them to predict demand, production volumes and more. Doing so, they can plan humam ressources and material appropriately to become more efficient.
We have several manufacturing plans, but I never know which one got capacity whenever we get a new customer order! What software should I implement?
Well this is a very difficult question to answer in a generic way. The first step here is to run a design-thinking workshop so that certain parameters and KPIs can be identified and agreed to determine the production plant utilisation score. From there each new order should be estimated based on the same scoring parameters and the matching algorithms need to be developed.
Waiting until machines break to fix them is too expensive. We need more preventive maintenance instead of reactive maintenance and I know that IoT could help us achieve this. But how could we start small with IoT without re-desining all processes and buying new machines?
More often than not, IoT is plug & play. Means, you can enhanced existing machines with IoT ready-togo modules that will work in background without affecting your existing processes.
Due to lack of demand planning, we are always producing the wrong quantities. Customers hates when we cannot deliver and start using alternative products. If we produce too much, we run into warehouse problems, working capital issues and ultimately we end up dropping prices. We need a much better forecasts! But how to achieve it?
A good forecasting requires strong tools to collaborate with your end customers but primarily with your sales teams.