IoT in Discrete Manufacturing
AXULUS Solution Templates for Discrete Manufacturing IIOT as a Service – Have you ever wondered how to start with digitalization? Are you curious how to generate value add for your customers or in your daily operations based on the newest digital technologies? With AXULUS Solution Templates it is easy to identify and customize value-adding IoT solutions for your benefit. Start from a library of quantified Use Cases and Solution Templates to customize and build your own Digital Solution Intellectual Property (IP). We can deliver the solutions customized for you as fully managed service (Industrial IoT as a Service by AXULUS) or use the Solution Templates for your own implementation teams or partners to deliver them to you IP.
Digital is the new Productivity Imperative in Manufacturing
It is well known that the main objective of Lean Manufacturing is to reduce waste and bring added value to the production process. However, the core principles of Lean can be improved when integrated with advanced software, sensors, any type of automation, robotics and other technologies powered by Internet of Things. This allows to monitor industrial machines constantly and in real time, take decisions faster and be more efficient.
The integration of IoT with Lean Manufacturing allows to take this methodology to the next level.
Information gathered from connected devices can be leveraged to improve manufacturing processes and reduce waste within any manufacturing plant.
AXULUS USE CASE LIBRARY
CONDITION MONITORING
IoT Condition Monitoring solutions enable manufacturers to take fact-based decisions, prevent the need of costly maintenance actions, minimize impending risks of failure and guarantee higher safety.
Machine Data Acquisition to optimize OEE
The analysis of machine data allows to acquire knowledge on availability, quality and performance of the production lines, identify potential improvements and plan the machine optimisation based on specific KPIs.
Sensor-based in-line Quality Inspection
IoT sensors are used to constantly monitor and control machines and parameters that directly impact the quality of a product, increase machine reliability, deliver a high level of scalability, cost-efficiency and interoperability.
Root Cause Analysis of Quality Deviations
Automated Root Cause Analysis allows to detect safety issues faster, identify complex process disruptions and predict quality deviations to prevent the waste of raw materials.
Digital Shopfloor Board
Visual Performance Management solutions provide real-time information on production measures, create visibility of your manufacturing process from shopfloor to boardroom and helps preventing waste and focusing on the critical areas to reduce cost in your operations.
Predictive Maintenance
Data captured by IoT sensors connected different assets enable businesses to predict, plan, and take proactive steps, contributes to increase asset utilization and extend their life, improve field crew efficiency and reduce maintenance costs.
Digital twin of production equipment
A Digital Twin consists of the virtual representation of a physical product, augmented by real-time process data and analytics based on accurate configurations, which can be used to monitor and optimize the product availability and performance.
Autonomous Robots
By integrating autonomous robots to a central server, it´s possible to automate tasks intelligently with minimal human input, such as the transportation of materials across the factory floor avoiding obstacles, coordinating with fleet mates, and identifying where pickups and dropoffs are needed in real-time.
IOT Asset Tracking
Through connected devices, sensors and data analytics, IoT Asset Tracking enables the remote monitoring and the geo-localization management of a valuable property, such as manufacturing equipment, car or truck fleets or even livestock on a farm.
These are only few of the Use Cases you can find in the AXULUS Library. To have full visibility on the solutions proposed by us and our ecosystem of Partners, please contact us.