IRS e National Instruments saranno relatori al convegno scientifico dedicato a Robotica, Visione, Motion e IIoT il pomeriggio del 24 maggio.
Il convegno scientifico dedicato a Robotica, Visione, Motion e IIoT , moderato dal Professore Claudio Melchiorri (Università di Bologna), si terrà nella Sala Cioccolato, padiglione 7, dalle ore 13.50. Il tema della relazione tenuta da IRS e National Instruments è “Automated test revolution in manufacturing, how enabling technology are changing the appearance and the soul of test workstation“.
Il programma dettagliato del convegno è disponibile a questo link: programma dettagliato convegno Robotica, Visione, Motion e IIoT a IIoT. Passate a trovarci o richiedete una copia delle slides della presentazione: firstname.lastname@example.org . Altrimenti ecco l’abstract della relazione:
In manufacturing, products are tested for statistical, quality, energy or safety standard compliance. These tests are made at different stages. At design stage to verify and improve prototypes. In production, to verify manufacturing quality and standard compliance. These tests are best accomplished by using automated test stations. These test stations are usually prepared by internal department or external system integrators using an architecture composed by sensors for measurements, PLC for data acquisition and control, PC and monitor, a database for results collection and statistical calculations.
It is a proven solution but it suffers some evident drawbacks. It is a local solution, and local in different perspectives. Local in space: it doesn’t talk to other similar test facilities in other manufacturing plant or even in the same location. Local in time: tests are not linked to other similar tests made the days or the years before. Local in parameter logging & control algorithm: environmental and operator related parameters are not taken into account, higher level of batch and operator scheduling are not taken into account in the control loop.
It is also a dumb automation: local parameters and local information in space and time translates in sub-optimal test speed, accuracy and resource allocation.
New enabling technology allows a revolutionary change to this aging architectures. Three are the main drivers.
The first is a push from local to global. Cloud allows a sudden and easy expansion of the test workstation horizon: from a local test to a global fabric of workstation facilities, integrated and talking each other. Huge data-set both internal and external can be accessed globally, queries are as fast as a search with Google .
The second driver is from dumb to smart. Using the large data-sets available and new artificial intelligence technologies we will experience faster tests thanks to:
- better control algorithm (human operator can be replaced in many/all activities)
- prediction algorithm can anticipate test results (faulty product do not need to fail)
- test sequence and time schedule can change as function of environmental parameters as well as human operator
The third driver is human – machine interface. Thanks to mobile and wearable devices look and feeling of test workstations will change. First, information will be available everywhere on mobile and tablets. Second, different information will be incorporated in new device family like smart glasses and smart watches. Third, information will pop up when needed. Based on user role and location different test control action, supervisory alert and tailored analysis will pop up to the right person at the right moment.
How to manage these three drivers? Our answer is using the power of platform. In a world moving fast it’s fundamental to anchor to platforms. They can provide flexibility in choice and a well-developed partner ecosystem to deliver niche solution.
An example of next generation automated test solutions is our HVAC life test workstation. It combines data results from large datasets, use machine learning algorithm for predicting test results before failure and show test results to supervisory operators using smart glass or mobile application.