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68 SMT007 MAGAZINE I APRIL 2018 also will provide insight into what changed, enabling maintenance personnel to fix the problem faster. Not only will adding automatic profiling improve the reflow process, but the entire production line uptime will increase due to faster troubleshooting and elimination of manual tasks. The average manufacturing engineer spends 40% of his/her time looking for equipment, personnel, information, etc. Again, profiling is a contributor. There are multiple profile tasks for multiple jobs over multiple ovens. The new industry trend of producing products in larger varieties builds further complexities. Central- izing all reflow (wave, select) data in a single database allows the engineer to manage and retrieve the exact data required with a few mouse clicks on any authorized PC or mobile device. Relevant data for each PCB produced becomes available in seconds. Smart factories make good use of machine and process data to run their operations more effectively. Adding analytics to thermal process data enables a higher level of automa- tion and productivity. For example, an intel- ligent database that learns the relationship between each assembly, process window and oven properties can eliminate or reduce the need for manual profiling. Entering a new PCB assembly length, width and weight into the software will produce a recommended opti- mal setup. Data analytics promises predictive process control and preventive maintenance to further enhance productivity and advance- ment towards the zero-defect goal. The data will not only be used to sub-optimize the ther- mal processes, but it can be shared with other machines and MES systems via the factory network to optimize multiple lines as well as the whole factory. Figure 1: Several moving parts form an ecosystem.

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