Real time data collection allows for immediate action for defect prevention and troubleshooting, thereby saving time and money for rework, trash or field failures. Again, analysis then leads the way to corrective action and improvements, a more efficient process with less scrap, rework and times savings, bottom line, save money. The analysis of the data provides deep insight into the process, shows where problems occur, why and how often, managing the product’s quality. Mentor, a Siemens business, states that ‘The key to avoiding problems is to analyze all available data intelligently, particularly in critical areas.’ Having the ability to identify each step of the manufacturing process allows for fast troubleshooting should a problem occur, whether during production or in the field. Now traceability has become a requirement, especially for customers who inquire about the systems that were used for their product assembly and any problems associated with them, particularly for liability requirements.
The manufacturer, and most importantly the customer requires complete product information.
Data Collectionĭata is being collected in factories now from incoming inspection, inventory and throughout the manufacturing process and further to product reliability in the field. However, implementation of this technology completes the data collection protocol. Some use AOI post reflow but then you’re too late, requiring rework or scrap.
Data analytics is being collected at the print process and then nothing for the reflow. This data was the ‘black hole’ in manufacturing data collection and therefore true process control, troubleshooting, traceability and optimization was incomplete. This is done via automatic profiling, a technology that is >40 years old and used by manufacturers around the world who produce product from commercial/consumable electronics, cellular, automotive, medical, mil-aero, and more. Use of this information in real time is used for quality assurance, quality improvement and process control. Existing technology can be used to monitor, track, document and react to production during the reflow process. One area of the manufacturing process that is often overlooked is the reflow process. This does not mean the collection of all data that becomes a mass of space but rather the product and process data that can be easily analyzed, and often live for fast reaction. Useful data is imperative to clear insight, correct decisions and optimization. Introductionĭata is the foundation of a smart factory. Key words: Automatic Profiling, Solder Reflow, Smart Factory, Process Control. Ask any CQE or Quality Engineer, they need data to support any process changes or customer complaint. An automatic profiling system (reflow process inspection) will automatically collect the thermal data at the board level for precise process control and allow traceability for every board that has been through reflow with the actual Thermal Profile, SPC, and Cpk stored for every board. This paper will talk about the reflow oven and how automatic profiling has also become a necessary tool for data analytics and troubleshooting as well as taking the guess work out of oven profiling.
We have even put a great deal of technology into the back end of the process with (AOI and X-Ray) to look at every solder joint and void the board may have. We are concerned about the printing process for precise volumetric printing to the point where Solder Paste Inspection (SPI) equipment has almost become a standard on the surface mount line. There has also been a great deal of focus on the front end and the backend data for the SMT process. Data analytics has become paramount and anyone that is collecting the correct data will have proper process control to support SPC, Cpk, and Ppk data to suffice customer requirements. With the advent of i4.0 and Smart Factory, there has been a great deal of technology put into SMT lines that are manufacturing the very technologies we use today.