INDUSTRIES AND USE CASES
Solutions
TIM’s core functionality for advanced forecasting and
anomaly detection can apply to a broad range of industries
and use cases. However, our initial focus is on the following
applications.
TIM’s core functionality for advanced forecasting and
anomaly detection can apply to a broad range of industries
and use cases. However, our initial focus is on the following
applications.
The energy market is a complex web of suppliers, grid
operators, utility companies and brokers, all of which are
under pressure to act smarter, cleaner and more efficiently to
meet the world’s energy demands. Accurate forecasting is
essential to keeping the grid balanced, reliable and to
maintain the best pricing for business and consumer rate
payers. There are many applications for AI in the “smart
grid” of the future but here are some of the pressing
problems for today.
Demand & load forecasting for electricity, gas, heating and cooling operators, and
distribution network operators.
Business managers at B2B and B2C energy suppliers need to make timely, accurate predictions of electric/gas/thermal energy consumption to avoid the costs and risks associated with system imbalances.
TIM automatically creates predictive models for each customer or group of customers that can accurately forecast consumption for the days/weeks/months ahead.
Improves forecasting accuracy by as much as 20% to enable more aggressive pricing, winning more clients and maintaining consistent profit margins – which can translate into hundreds of thousands of euros per year.
Supply forecasting for renewable energy plants such as
solar, hydro and wind.
Utilities are continuing to shift from their supplies from fossil fuels to renewable sources of electricity, but they all suffer from significant variability due to time of day, weather and seasonal changes. Oversupply and undersupply of power create system imbalances that must be compensated for.
TIM automatically creates accurate predictive models for each asset, helping utility companies, grid operators and energy suppliers plan their portfolios on a daily basis.
Avoid imbalance costs and optimize the use of renewable sources despite their inherent variability.
Price forecasting for energy trading.
The rapid rise of renewables and an increasing number of market players have made energy markets extremely volatile. Understanding short term and long term price trends is crucial to avoid trading and nominations on moments of high prices.
TIM seeks patterns in historical price fluctuations and the relationship of other variables to the price trends. It provides traders with an accurate predictive model and an understanding of the dynamics of price variability.
Make better trading decisions based on sophisticated mathematical models without the need for a team of Machine Learning experts.
Anomaly detection and predictive maintenance for
power generation equipment.
Unplanned downtime, efficiency degradation and routine maintenance cycles are all significant costs for energy suppliers and impact the reliability and cost effectiveness of their service. Most companies don’t have the resources or know-how to implement predictive maintenance so they rely on fixed maintenance cycles and reactive equipment repair.
TIM can analyze historical data from equipment and sensors to spot anomalies and cause-effect relationships that can be used to optimize maintenance cycles and avoid unplanned downtime.
Improved equipment reliability and optimized maintenance cycles, without the need for extensive machine learning or data science expertise.
In asset-intensive manufacturing operations, Overall Equipment Effectiveness (OEE) and quality are key competitive advantages that can have a significant impact on your bottom line. Traditional reactive and fixed-schedule approaches to maintenance and quality control are no longer yielding significant improvements, and companies must adopt AI technologies to get to the next level. But most companies lack the resources and expertise to tackle the problem so it often takes a back seat to firefighting activities. That’s where Tangent Works can help.
Anomaly Detection
How to spot anomalies in the time-series data collected during the manufacturing process that can act as early indicators for equipment malfunctions or quality degradation- while minimizing false alarms.
Use TIM to identify patterns and cause-effect relationships in your equipment and sensor data. Integrate TIM with your data historian to create a continuously updated model that can predict anomalies before they occur.
Improved equipment reliability, optimized maintenance cycles, improved product quality- all without the need for extensive machine learning or data science expertise.
Predictive Maintenance
How to determine the optimal time to perform routine maintenance, refurbishment and replacement activities on manufacturing equipment without the need for extensive data science and machine learning expertise.
Use TIM to analyze the time-series data you have accumulated from your manufacturing equipment and IoT sensors. TIM will build individualized predictive models for each asset and for entire production lines to help anticipate when failures or degradations are likely to occur and help you optimize your maintenance cycles to avoid unplanned downtime.
Reduced downtime, lower maintenance costs and improved product quality.
The Challenge — How to leverage AI technology to improve operational efficiency.
Forecasting and anomaly detection are essential for most businesses since managers must always try to match supply and demand and make their operations run as smoothly and
The Challenge — Meeting the demand for AI-based
forecasting and anomaly detection.
Your organization would like to jump on the AI bandwagon but there is a shortage of data scientists and there’s a tremendous backlog of projects awaiting resources. You’d like to be able to innovate and leverage AI/machine learning technology without needing to be an expert.
TIM delivers — Accessible, accurate AI with fast time to
value.
TIM automates the model generation process so you can create and update predictive models without being an AI expert. So instead of using one generic model to fit a class of customers or equipment, you can create individualized models for each customer or asset, and get the best possible accuracy.
The Challenge — Hosting compute-intensive AI tools and integrating them with your existing databases and applications.
Some AI tools are very compute-intensive and require a major investment in on-premise hardware or cloud instances. You’ve likely got plenty of existing databases, data historians, BI tools and enterprise applications that would likely need to interface with a new predictive analytics tool. Firewall restrictions may make cloud-based solutions impractical.
TIM delivers — maximum compute efficiency, rapid integration and flexible deployment options.
The Challenge — Improving your productivity so you can
focus on the most important tasks.
It’s hard to recruit and retain data scientists these days so your job security is better than ever. That’s the good news. But with a long list of potential AI use cases in your company you may not be able to get the help you need to scale up the use of predictive analytics beyond a small number of projects.
TIM delivers — Scalable, automated, understandable AI
TIM Improves your productivity by eliminating repetitive, trial-and-error modeling tasks and by helping you visualize your model with an intuitive heat map that shows the relative influence of all your input variables. Unlike other modeling tools that require you to choose from
hundreds of pre-defined models, TIM creates an optimized model based on the patterns it detects in your time-series data. You’ll spend less time doing feature engineering, building and explaining models and more time on exploiting the power of predictive analytics across your organization.
