Here is the analogy: What if a refrigerator sensor could detect energy consumption above the model rating and then do a little detective work. Is the temperature setting too low? Is the door being opened more times a day than the industry standard? If that’s the case, the manufacturer can send the owner tips to reduce the energy bill. Or maybe the sensor shows temperature and usage are normal, but the compressor is cycling too frequently. A remote software update to reduce compressor cycles and a note to the customer could solve the problem.
Identifying issues in small subsets of the product population is a key to improving quality for diverse issues. Connected device data allows the detection of ubiquitous issues even more quickly and accurately. As the result, issues are contained proactively and customer dissatisfaction is prevented.
The analytics application to data as it streams off production equipment sensors would allow manufacturers to sense and predict output variation. In a networked manufacturing environment (a.k.a M2M), the machine can communicate its output variation to downstream equipment, which automatically makes adjustments to ensure the final product is within specifications.
Sensors help determine the right time for service. By properly analyzing the informations, companies can design service contracts that make money for the organization and save money for the customer. This service contract can be beneficial for both parties.
Product managers and designers have relied on sample data through interviews, surveys, focus groups and teardowns. With sensors embedded in everything that leaves the factory, it will make identification of users new segments easier. This will lead to new segments and new features to create more value for customers, increasing customer loyalty and revenues.
Surely, connected devices will reshape manufacturing. But sensor data doesn’t do any good without an analytics platform to help make sense of the data. This platform needs strong data management capabilities, querying options that a business user can manage, and (where appropriate) live event streaming that does the analysis as the data is collected avoiding the need to store and organize it.
Source: Industry Week