One of the great things about working at Yellowfin is the partnerships we forge with other businesses, and being able to bring the benefits of our solution to a wider range of industry sectors. Over the coming months, I’ll be looking at how our partners integrate Yellowfin’s Business Intelligence and analytics capabilities into their solutions to deliver some inspirational data product offerings.
Today, I want to introduce our new partner, Valuable Data, who is focused on addressing manufacturing clients’ industry challenges. What I like most about Valuable Data’s approach is that they have developed a really innovative Predictive Maintenance solution that packages smart AI capabilities with Yellowfin analytics to deliver a cutting-edge proposition that’s accessible to all manufacturing firms, large and small.
Challenges in the Manufacturing Industry
Recent Manufacturing industry surveys have shown sobering figures about the impact of machine downtime. In Britain, unplanned downtime is costing manufacturers more than £180bn every year (Oneserve). Across the pond, suboptimal maintenance strategies are reducing production by 5-20%, with losses of $50bn p.a. (Wall St Journal).
Lots of factors can contribute to downtime. Lack of staff training and incorrect machine usage, aging equipment, vandalism, accidental damage and power issues all spring to mind. The overriding causes, though, are hidden internal faults and inefficient maintenance schedules. For manufacturers, it’s a constant balancing act between avoiding costly breaks in production and maximising the lifecycle of their machines and components.
The main issue is visibility. Without the proper technology, it’s impossible to get an accurate view of the condition of every part of a machine. This poses a dilemma. Manufacturers could keep using the parts until they give out, but, while this maximises the part lifecycle, it risks breaking the entire machine. Alternatively, they can ensure that parts are replaced, and machines are sent for frequent planned maintenance. This is expensive and leads to intolerable levels of planned downtime while increasing the risk of bad procurement decisions and poor inventory.
The Path to Predictive Maintenance
Maintenance planning has developed from reactive (too little too late) to preventative, based on factors like age, mileage, and use. This requires a lot of manual historical data analysis just to see why the downtime has already happened and prevent it next time. It takes too long to get to any actionable insight and can’t keep pace with the rapidly changing requirements of new technologies.
Fortunately, the new solutions incorporating Internet of Things (IoT) -connected sensors and real-time Business Intelligence analytics, are enabling manufacturers to move to a more accurate, Predictive Maintenance model.
This is why Yellowfin has partnered with Valuable Data, an innovative new business created by a highly experienced team of IoT and Data Experts, to create a Predictive Analytics solution that maximises on the value that AI has to offer.
Valuable Data’s AI solution is based on innovative algorithms that allow:
– Automatic segmentation of the signals coming from both the sensors on the assets and from the operational system
– Analysis of the particular condition that the machines are in at a specific time, and the transition between the relevant stages.
So, when a new condition or a new transition is detected, the operator is automatically alerted and can assess the situation. Whatever happens, the system becomes refined by the assessment so it only needs to highlight the issue once. If a new condition indicates a malfunction, a maintenance requirement is automatically flagged according to the risk of failure within a defined period of time (3, 7, 14, or 21 days).
What is particularly interesting is that these algorithms work in real time, they do not need to store data or rebuild an analytical model. Their effectiveness is quite remarkable: they can detect 90% of breakdowns before they occur.
Yellowfin, as a visualization layer, allows the user to have a clear and intuitive view of the risk of breakdowns and the associated costs, through scorecards and dashboards built from the raw data coming from the sensors and the IT systems, all of which can be created without specific technical skills. The collaborative features embedded natively in Yellowfin, enable end users to share this information internally which is hugely advantageous.
A Solution with 3 Business Models
What we love about the Valuable Data solution is that it goes several steps further than the other predictive models on the market. IoT sensors are placed on components, partially finished products and the end product, to detect any anomalies in critical breakdown factors like temperature, speed, vibration, and movement. With Yellowfin reporting directly on this data, this information can be analysed in real time, enabling insights driven decision-making and Predictive Maintenance schedules. This intelligence can also be combined with data from with ERP and CMMS systems.
In addition to real-time visibility, accuracy, and scalability, Valuable Data offers a further competitive advantage by enabling manufacturers to move to a service-based model, whereby they monitor and manage the performance of their products at their clients’ sites. The third way that manufacturers can capitalise on the solution is by sharing these valuable insights with the wider business community.
Other Competitive Differentiators
Valuable Data’s predictive maintenance solution is targeted at the SMB market, unlike most solutions on the market that mainly target large enterprises. Available within a Software as a Service (SaaS) model, it requires no installation client side, so they can focus on their core business. It was built with the input of a user base of five early adopters – who have contributed to ensure it delivers a high level of user experience and ease of adoption. Since it is based on open technology standards, it easily integrates into any company’s technology stack. As mentioned previously, this approach has been proven to detect and anticipate up to 90% of outages, with the remaining 10% being false positives.
Valuable Data not only provides a simple software solution to a very complex and expensive problem, but they accompany their customers on the ‘value chain’ journey: identifying the data to be analysed, installing the sensors and monitoring data collection, analysing the throughput of data from the predictive maintenance solution to the overall piloting of the project, and of course, any change requests or support required.
Business Benefits at a Glance
- Efficient, reliable asset management and optimised lifecycle to meet SLAs
- Significant reduction in planned and unplanned downtime
- Improves reputation and customer loyalty
- Adds value by passing the solution onto customers as a service
- Increases market share, recurring turnover, and operational margin growth
- Improves safety and helps meet regulatory requirements
- Covers the entire value chain with a value-add at each stage
- Multi-layered security at the sensor, data processing, and product level
- Helps R&D to improve asset liability
An Innovative Team
In addition to the considerable business benefits of the solution, Valuable Data is a highly experienced, innovative team of genuinely nice people, with excellent credentials and proven track records.
Co-founder Franck Chekki, in charge of Marketing & Sales, gained his experience at T-Systems and Capgemini, while co-founder Marc Daverat, in charge of Operations & Solutions, gained his at Capgemini and Deloitte.
Co-founder Olivier Arnould is a partner at Acumeo, which specializes in change management, and Co-founder Emmanuel Gavache is the CEO of Eridanis, an IoT expert company.
The whole team clearly love what they do and are constantly striving to create innovative solutions that benefit their customers. This matches the Yellowfin work ethos, so partnering with them was a no-brainer.