e.preventDefault(); // Prevent form submission input.blur(); // remove focus input.value = ""; // optional: clear the input

Case Study

AI/ML Case Study


Shell (MachineMax)

The collaboration between MachineMax and Tudip Technologies delivered an innovative IoT and AI-powered solution that transformed machine operations at mining sites.

At a Glance

Shell recognized the potential of MachineMax’s solutions and acquired the company to support its goals of reducing carbon footprints, improving operational efficiencies, and enhancing sustainability initiatives.

Challenges

MachineMax wanted to enhance its IoT-driven platform by incorporating advanced analytics to provide deeper insights into machinery performance. 

Their goals were to:

  • Monitor machine health and performance with real-time data on vibration and temperature.
  • Reduce carbon footprint by minimizing idle time and optimizing usage.
  • Increase machine and labor efficiency, ensuring better productivity and safety.
  • Improve decision-making capabilities for managers and executives by providing actionable insights from IoT data.

Solution

Tudip Technologies worked closely with MachineMax to implement an intelligent data analysis solution that would revolutionize the way machine data is captured, analyzed, and utilized for decision-making.

 

  • IoT device integration on heavy machinery: MachineMax placed IoT devices equipped with sensors on heavy machinery at various mining sites.
  • Data analytics with Tudip’s AI algorithm: A sophisticated AI algorithm to process, analyze, and extract meaningful insights.
  • Reducing carbon footprint: AI-driven insights helped companies monitor fuel consumption and idle times.
  • Increasing machine & labor efficiency: The IoT and AI system for better improvements in machine and labor efficiency.
  • Enhanced decision-making across the board: Detailed operational data for field managers to high-level KPIs for executives.

Results

MachineMax, with Tudip’s AI and IoT expertise, achieved remarkable outcomes:

 

  • Improvement in Machine Efficiency: By identifying and rectifying inefficiencies, the IoT data-driven approach improved the operational efficiency of heavy machinery, reducing fuel consumption and downtime.

 

  • Reduction in Carbon Footprint: The optimized use of machinery and reduction in idle times led to a reduction in carbon emissions, a key metric in meeting sustainability goals.

 

  • Increased Labor Productivity: With the right machinery in the right place at the right time, labor productivity saw a significant improvement, leading to better project outcomes.

 

  • Informed Decision-Making: The AI-powered analytics provided clear, actionable insights, improving strategic decision-making for both operational managers and senior executives.

India

Plot No. 11/2, Phase 3, Hinjewadi Rajiv Gandhi Infotech Park, Pune, India – 411057.
info@tudip.com
+91-96-8990-0537

United States

1999 S. Bascom Ave Suite 700, Campbell CA. 95008, USA.
info@tudip.com
+1-408-216-8162

Canada

64 Caracas Road North York, Toronto Ontario M2K 1B1, Canada.
info@tudip.com

Mexico

Calle Amado Nervo #785 Interior B Colonia Ladron De Guevara 44600 Guadalajara, Jalisco, Mexico.
info@tudip.com

Colombia

Cra. 9 # 113-53 Of. 1405 Bogotá D.C., Colombia.
info@tudip.com

UAE

Tudip Information Technologies L.L.C Office No 109, ABU HAIL BUILDING 13, Abu Hail, Dubai, UAE.
info@tudip.com

Nigeria

22 Kumasi Crescent, Wuse 2, Abuja, Nigeria.
info@tudip.com