The Nytt way to a more efficient production is
straightforward.
First, you should agree with
some basic facts listed below.
That means we set goals and make timetables for when to
achieve these goals. We will create a budget and timeline to
check on expectations, and if not met, we will make required
corrections.
Our experience is that we start with a limited number
of machines/equipment that we monitor. We agree on how the
data should be collected and make the suitable
installation.
Then we start collecting data from the units, and
after about 3-4 weeks, we have enough data to see clear
trends/patterns of how efficiently they are used and come up
with the first set of recommendations on how to improve.
In parallel, we also do basic training for the operators
involved and give them our OpApp. The operator App provides
additional information that we cannot get directly from the
machines. The OpApp also sends information to the operator to
inform them of the live situation to help act accordingly (shop
floor driven).
When the first data gathering is done, with the help of our
Dashboard, show the data obtained and show what conclusions can
be derived. We usually find 3-20% improvement potential with
minor changes in this first stage.
After this first period of low risk for our customers, we sit
down and set a strategy on how to proceed. That includes more
data gathered from the machines connected and maybe increasing
the data gathering points within them to get an even better
picture. But importantly, we decide how to address other
machines/equipment in the factory. We always have a step by step
approach in mind, to not overload in the first step.
Experience shows that in the beginning to get started, our help
is required, so we provide expert advice through experienced
production engineers. The goal is always that the customer
should gain enough experience to use the Nytt system to make the
necessary improvements by themselves.
Nytt is driven by production people. We have backgrounds in
manufacturing, supply of production equipment such as
machine tools, tooling, and theoretical knowledge within
academia.
Our drive is to increase productivity and effectiveness in
manufacturing.
Our firm conviction is that the way forward is to collect as
much data from as many sources as possible, analyze it in a
simple and streamlined way, and top it with ML functions to
see what is happening now and look into the future.
We have created a data-driven platform for manufacturing
companies to have flexibility in decision-making. Using our
platform that collects real-time data from the machines, the
operators, and other critical sources on the shop floor, we
provide relevant information to make data-backed decisions.
We also use the historical data to find repeating patterns
and provide information regarding any anomalies regarding
how a piece of equipment is working, helping manufacturers
anticipate and adapt to failures and downtime before they
occur.
Using different data-collection strategies through readily
available equipment like smartphones, sensors and standard
machine protocols, we can get a clear idea about how a
factory is running. This information helps companies plan,
check, and adapt to the rapid changes and make informed
decisions to become more profitable.
We understand that different companies need different solutions, which is why we also offer customized solutions through our IT consultancy service Nytt IQ. We help businesses with system development and integration and we develop solutions involving data analytics. Visit Nytt IQ to learn more about our services and book a consultation.
ME in Production Engineering from KTH Royal Institute of Technology and MBA from Insead France. Previously CEO at Wikman & Malmkjell AB and now CEO at Precima Production AB.
M.Sc. in Production Engineering from KTH Royal Institute of Technology. Working with Scrum and design thinking.
M.Sc. in Production Engineering from KTH Royal Institute of Technology. Working with R&D and digital solutions in manufacturing.
Experience in machine learning and data science. Working with machine learning strategies in manufacturing.
Former senior research fellow at KTH Royal Institute of Technology, Department of Production Engineering, Stockholm.
Team of 15 programmers in India, working with UI, analytics, web, and Android.