Post by guest blogger, Mikhail Lakirovich, IBM Market Manager
Driving along California Highway 1 was an exhilarating experience…Fresh ocean air, turquoise water, blue sky, and plenty of memory making photo opportunities promised this to be a pleasant change from the usual Chicago scenery. The trip was perfect…up until when we boarded the place for our flight home.
After boarding, my girlfriend and I found out that the crew was late, so we sat in the stifling hot airplane (the air conditioning was turned off because it was in what was explained to us as “ground mode”) for an hour. Upon the crew's arrival, we spent an extra hour, waiting for the mechanic to work on the air conditioning that refused to cooperate – there was some 'electronics' issue. With the large number of passengers with tight international connections, the crew made the executive decision to not spend more time on the air conditioning in the cabin and take off. Spending four hours in a pressurized airplane without a cool wisp of air, while wistfully remembering the drive along the ocean with open windows was far from being an enjoyable experience. And, no, the water distributed by the crew throughout the flight did not alleviate the discomfort leaving everyone oddly dreaming of fresh O’Hare International Airport air that's far from ideal.
The heat, instead of making passengers hostile towards each other, actually united them as they discussed the situation and expressed their displeasure. It was only logical to assume that many of these passengers would spread the word of their experience to their social circles. It would not be long then up until some of that customer experience resulted in lost revenues for the air carrier as the disgruntled flyers take their getaway flight with a different company. But I digress…
As I was sitting in the cabin, I wondered about the reactive approach to the problem. The air conditioning would not work, so the mechanic was sent to fix the problem. Once he or she was unable to do so, the decision was simply to fly anyway. Wouldn’t it be great, though, if this paradigm were reversed and the problem, along with its root cause, was identified BEFORE we boarded the plane? How much customer satisfaction and revenue with this air carrier retain if it were able to predict the likelihood of faulty air conditioning and electronics on that aircraft?
Problems similar to these are a common place occurrence for organizations in such industries as transportation, automotive and electronics as they have to deal with asset quality and detecting issues on the production line. They have to continuously struggle with such questions as “Are these parts the only ones that are faulty or is the entire batch at risk?” Answering this question and implementing tests can be a time-consuming and cost-prohibitive process.
In a response to these concerns, IBM has created a solution that allows organizations to harness the power of data stored in their systems and translate it through predictive analytics into actionable insights by uncovering hidden patterns and trends.
Today, we are excited to announce that our 2nd version of our product, IBM Predictive Maintenance and Quality (PMQ), is now available. It is a pre-integrated, pre-packaged, cross-brand solution that enables organizations to reduce costs, increase productivity and improve quality and efficiency by:
Monitoring, maintaining and optimizing assets for better availability, utilization and performance
Predicting asset failure and identifying poor quality parts earlier to better optimize operations and supply chain processes
Reducing guesswork and incorporating experiential knowledge during the decision-making process
The product includes data schemas, predictive models, dashboards and scorecards to provide you a strong head start to accelerate your client’s time-to-value. Additionally, it includes intellectual property from IBM, such as a quality early warning algorithm, which enables clients to identify poor quality issues much sooner than traditional statistical process control methodologies.
IBM implemented PMQ technology in its own manufacturing process to identify faulty patterns and predict outcomes with the goal of minimizing inspection costs and improving efficiency of production.
The results have been huge:
97% fault recognition for one specific operation potentially avoids hundreds of thousands of dollars in total costs;
150% ROI expected from fault pattern recognition analytics; and,
160% ROI expected from improving product quality by controlling humidity.
MORE PMQ RESOURCES
For more information on the implementation of this solution, please see the IBM Bromont case study.
Meanwhile, please join us on June 10th in Indianapolis for “A Taste of Analytics: Discover the Business Value of Predictive Maintenance” events!
Also, please register to attend our June 25th webinar, which will cover two Predictive Maintenance case studies – Daimler and IBM Bromont.
Lastly, please visit the PMQ webpage to learn more about this solution.