Splunk Case Studies Honda's Predictive Analytics Revolution: Boosting Profitability and Efficiency

	Honda's Predictive Analytics Revolution: Boosting Profitability and Efficiency Splunk

Honda's Predictive Analytics Revolution: Boosting Profitability and Efficiency

Splunk

Technology Category	Analytics & Modeling - Machine Learning Analytics & Modeling - Predictive Analytics
Applicable Industries	Electrical Grids Equipment & Machinery
Applicable Functions	Maintenance Product Research & Development
Use Cases	Onsite Human Safety Management Time Sensitive Networking
Services	Data Science Services Testing & Certification
Challenge	Honda Manufacturing of Alabama (HMA), the largest light truck production facility of Honda, was facing a significant challenge in terms of data utilization. Despite generating a vast amount of data from the assembly floor, the plant lacked the ability to leverage this data for insights into parts, equipment, and machines. This lack of visibility forced the team to adopt a reactive approach to troubleshooting, which was inefficient and often led to machine failure or interruptions in the production line. The inability to predict and proactively address issues was hindering the plant's efficiency, safety, and profitability. Read More
About Customer	Honda Manufacturing of Alabama (HMA) is Honda's largest light truck production facility in the world. It is the sole producer of Honda's Passport SUV, Odyssey minivan, Pilot SUV, Ridgeline truck, and the V-6 engines that power them. The factory employs over 4,500 employees who work with a complex fleet of machinery to assemble cars from hood to hubcap. This includes building frames, painting car bodies, and intricately placing thousands of parts within each vehicle. The facility is known for its meticulous production process, which generates a significant amount of data. Read More
Customer Name	Honda Alabama Read More
Solution	To overcome these challenges, Honda of Alabama turned to Splunk, a software platform that uses machine learning, IoT, and predictive analytics to turn data into actionable insights. Splunk was integrated across the factory, enabling Honda to proactively identify and solve problems before they escalated. The software's predictive capabilities transformed the plant's approach to problem-solving and innovation. For instance, Splunk's machine learning technology was used to predict and monitor equipment temperature when burning paint fumes, ensuring compliance with environmental standards and preventing shutdowns. Furthermore, visualized metrics and contextual event insights facilitated more collaborative problem-solving, significantly reducing the mean time to repair (MTTR). Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Analytics & Modeling - Predictive Analytics

Applicable Industries

Electrical Grids

Equipment & Machinery

Applicable Functions

Maintenance

Product Research & Development

Use Cases

Onsite Human Safety Management

Time Sensitive Networking

Services

Data Science Services

Testing & Certification

Challenge

Honda Manufacturing of Alabama (HMA), the largest light truck production facility of Honda, was facing a significant challenge in terms of data utilization. Despite generating a vast amount of data from the assembly floor, the plant lacked the ability to leverage this data for insights into parts, equipment, and machines. This lack of visibility forced the team to adopt a reactive approach to troubleshooting, which was inefficient and often led to machine failure or interruptions in the production line. The inability to predict and proactively address issues was hindering the plant's efficiency, safety, and profitability.

About Customer

Honda Manufacturing of Alabama (HMA) is Honda's largest light truck production facility in the world. It is the sole producer of Honda's Passport SUV, Odyssey minivan, Pilot SUV, Ridgeline truck, and the V-6 engines that power them. The factory employs over 4,500 employees who work with a complex fleet of machinery to assemble cars from hood to hubcap. This includes building frames, painting car bodies, and intricately placing thousands of parts within each vehicle. The facility is known for its meticulous production process, which generates a significant amount of data.

Customer Name

Honda Alabama

Solution

To overcome these challenges, Honda of Alabama turned to Splunk, a software platform that uses machine learning, IoT, and predictive analytics to turn data into actionable insights. Splunk was integrated across the factory, enabling Honda to proactively identify and solve problems before they escalated. The software's predictive capabilities transformed the plant's approach to problem-solving and innovation. For instance, Splunk's machine learning technology was used to predict and monitor equipment temperature when burning paint fumes, ensuring compliance with environmental standards and preventing shutdowns. Furthermore, visualized metrics and contextual event insights facilitated more collaborative problem-solving, significantly reducing the mean time to repair (MTTR).

Impact #1	The implementation of Splunk has brought about a transformative change in Honda's operations. The predictive capabilities of the software have enabled Honda to shift from a reactive to a proactive approach, significantly reducing the frequency of unknown incidents and midnight troubleshooting calls. The software has also facilitated cross-departmental collaboration, allowing teams to work together to solve issues faster. Moreover, the use of Splunk has led to a reduction in energy consumption and has freed up employees to focus on more strategic initiatives. In terms of safety, Splunk has been instrumental in tracking quality and upholding Honda's safety standards, ensuring the production of almost perfect products. The software has also been crucial in driving profitability by predicting equipment failure and enabling preemptive repairs, thereby saving significant costs associated with equipment downtime.

Impact #1

The implementation of Splunk has brought about a transformative change in Honda's operations. The predictive capabilities of the software have enabled Honda to shift from a reactive to a proactive approach, significantly reducing the frequency of unknown incidents and midnight troubleshooting calls. The software has also facilitated cross-departmental collaboration, allowing teams to work together to solve issues faster. Moreover, the use of Splunk has led to a reduction in energy consumption and has freed up employees to focus on more strategic initiatives. In terms of safety, Splunk has been instrumental in tracking quality and upholding Honda's safety standards, ensuring the production of almost perfect products. The software has also been crucial in driving profitability by predicting equipment failure and enabling preemptive repairs, thereby saving significant costs associated with equipment downtime.

Benefit #1	70% faster mean time to repair by expanding access to data
Benefit #2	Increased profitability and efficiency through better uptime
Benefit #3	Exceeded environmental standards by correlating machine, equipment, power, and IoT data

Benefit #1

70% faster mean time to repair by expanding access to data

Benefit #2

Increased profitability and efficiency through better uptime

Benefit #3

Exceeded environmental standards by correlating machine, equipment, power, and IoT data

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Overview

Honda's Predictive Analytics Revolution: Boosting Profitability and Efficiency

Operational Impact

Quantitative Benefit