Consumes machine data, shop floor data (structured and unstructured), and enterprise data in raw form. Contains relational databases from RDBMS, semi-structured data and binary data. Then, cleansing, de-duplication and aggregation of large amounts of data is performed so as to host a complete set of data sufficient for a 360-degree view of your factory.
We have a highly scalable streaming and analytics platform with pre-built models. Our Data Analysis Platform leverages Machine Learning, Deep Learning and KRR to deduce patterns based on historical data. It implements analytics and visualization use cases such as plant-wise performance and factors contributing to machine failure. The platform also offers insights to decrease downtime, identify risks and optimize machine efficiency.
Factory.360 provides a robust rules engine, workflow engine, visualization platform, ERP integration and dashboards with real-time metrics and views that you need for a 360-degree view of your factory. It also provides audience-based perspectives and actionable insights for each persona – Plant Manager, CEO, CFO, etc. For example, for a CIO can pull up a performance comparison across plants, a CFO can look at the macro factors impacting bottomline, etc.
Tracks all your IT and Non IT assets in one place establishing a clean baseline and tight control over your assets. IT assets are automatically discovered using our discovery engine. In sync with our workflow engine, our asset management platform lends itself to multiple automations such as change management, problem management, etc.
Ideas2IT’s Factory.360 platform has a suite of software for smart manufacturing. From asset management to Machine Learning, every module of the platform integrates easily with existing back-ends (MES, ERP, etc) and is customizable for individual factories. You can forever change the way your factory works. Use our platform for exclusive passes to a new era of digital manufacturing!
We leverage sound and vibration analytics to decide when a machine is working outside normal conditions. Then, we parse through thousands of data points using Machine Learning to understand which conditions really affect the state of the machine.
Our IIoT framework builds out Machine Learning models based on volumes of data. We use open-source scalable ML models like Spark MLlib and commercial offerings like SPSS from IBM or Azure ML for Microsoft.
Multiple sources can create a flood of noisy alarms. Our IIoT solution intelligently clusters the IT alarms/alerts and correlates into high-level related incidents know as ‘situations’, which are much easier to manage than thousands of disparate alerts.
Manual prioritization is subjective and often devolves into FIFO. Our IIoT solution automatically prioritizes incidents (or situations, once the incidents are correlated) by analyzing severity, level of disruption, incident duration, and other parameters.
Root Cause Analysis
Use Machine Learning to automatically sort through massive volumes of log messages and identify messages that are truly relevant. We use powerful analysis algorithms that self-learn over time, providing fresh insights to find the root cause of the problem every time.
Our Factory.360 platform is a comprehensive solution for the entire Industry 4.0 journey. These are some of the features guaranteed to usher your factory into the next decade of technical advancement.
Our Predictive Maintenance solution is built on an IoT platform. Its components can integrate seamlessly to any third party component. It augments ML to Knowledge Representation formalisms to perform smart logistics and forecasting. Pre-built model kits have regression and survival models, and our asset library consolidates and reconciles multiple asset data sources for up-to-date information.
Instead of looking at any event in isolation, Factory.360 analyses holistically and gives insights specific to each role. Performs multi-segmented analysis on the collected pool of machine, enterprise and factory floor data to give a multifaceted department-specific view: Financial Analysis for the CFO, Machine Capacity Analysis for the Plant Manager, WIP Inventory Analysis for the Floor Manager, etc.
Augmently.360, our AR-prototyping platform, bridges the gap between the Digital and Physical world. It leverages the richness of 3D and transforms users’ interaction with product. It supports users in product assembly and maintenance within batch production lines, provides on the job training by leveraging key workflows and procedures from existing technical publications, and aids selling by allowing interactive exploring of features.
Most companies that talk about industrial IoT talk about sensors, edge devices, data processing platforms and other tech. Not us. While we recognize that the tech is the means to an efficient end, it’s just that – a means. Ultimately, tangible business RoI is what truly drives transformation.
We understand that different stakeholders expect different outcomes – for example, a plant manager may want to minimize wastage, and make sure production lines are at maximum efficiency. A CFO, however, is looking at macro indicators from ERP and sales data, and needs to track financial performance. With Ideas2IT’s Factory.360 platform, every stakeholder gets to track factory performance using metrics that matter to them.
We aggregate shop floor data, ERP data, machine data and third-party data to create a 360-degree profile of the plant. Our platform opens up the factory to management in a lot more ways than just predictive analytics or time-series data would.
Our IIoT Center of Excellence provides services at the intersection of Data Science and Manufacturing, generating real-time predictions and improving the way organizations look at manufacturing. We will leverage our Factory.360 platform to help you predict and preempt breakdowns, gain strategic insight into product quality, decrease costs and risk, and meet compliance requirements.
At Ideas2IT, we learn every day. From product engineering to data science, from blockchain to chatbots, our experts discuss driving forces at the intersection of tech and business.
We look at business through the lens of technology, and break down how cutting-edge tech will alter the way companies in various industries operate. These are some of our learnings from working with factories and helping them along the Industry 4.0 journey.
Industry 4.0 Use Cases for Manufacturing
The first industrial revolution began in the late 18th century, with the mechanization of the textile industry. Nearly a century later, in the second half of the 20th century, the third industrial revolution appeared with the emergence of computers and the beginnings of automation, when robots and machines began to replace human workers on the assembly lines.
Condition-Based Maintenance Explained in Simple Terms
Condition-based maintenance (CBM) is about using the actual data gathered from the assets to decide what maintenance activity needs to be performed on the physical assets being monitored. In other words, it is a maintenance strategy that measures operational parameters in assets to determine a change in their condition, performing maintenance only when the need arises.
The Future: Convergence of IoT, AI, and Blockchain
The next big change that seems to be sweeping the industry is the triad of Artificial Intelligence, Internet of Things, and blockchain. Individually, these technologies seem to have endless use cases and possibilities. However, put them together and the transformative effect seems to become multifold, forcing us to extend our imagination and reimagine the art of the possible.