Developing a Strategy to Implement Smart Manufacturing March, 2018
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communication standard capable of supporting the detailed feedback required. In order to overcome the limitations of in-
line SMT equipment and harness the power of data to drive continuous improvement, Yama- ha developed its own machine communication interfaces. These interfaces facilitate the col- lection of rich data from machines in the pro- duction line and enable analysis and reporting or alerting in real time. Yamaha has helped manufacturers im-
prove quality control and boost productivity by identifying defects, such as missing components or incorrect alignment. This enables them to take remedial action immediately. Yamaha’s initiative also makes it possible to collect infor- mation capable of driving preventive mainte- nance, which is becoming an important part of smart manufacturing. Feeding solder paste inspection
data to the printer enables auto-cor- rection of print alignment and auto initiation of stencil cleaning. AOI da- ta gathered in-line, immediately af- ter component mounting, enables quick diagnosis of component place- ment errors or solder paste defects, down to the level of individual mounter nozzles or stencil apertures. Machine software is able to di-
agnose the exact causes of errors and send alerts to a mobile terminal, such as the supervisor’s smartphone, to help accelerate fault resolution, min- imizing line stoppages. This mobile decision application is only one part of Yamaha’s extensive Y.Fact soft- ware suite for optimizing setup and performance at machine, line, and factory level. Combined with individ- ual machine capabilities, this soft- ware provides a platform from which a smart manufacturing strategy can be launched and continuously ex- panded and improved.
Y.Fact Software
The four modules that make up Y.Fact software are known as P-Tool, M-Tool, S-Tool, and T-Tool. They handle data programming, line mon- itoring, set up navigation, and trace- ability, respectively. The P-Tool for data programming carries out actions that include CAD data conversion and reverse engineering of Gerber files to help save preparation time. Eliminating trial runs dovetails well with smart manufacturing ideals by saving materials and supervisor time and automatically optimizing and balancing the line. The line monitoring capabilities
of the M-Tool represent perhaps the most obvious area for software to support smart manufacturing. Dis- playing line and factory status with a web-based interface makes detailed information, such as efficiency, oper- ating ratios and pickup rates, avail- able to supervisors in real time. Color-coded status indicators
enable simplified monitoring of the line. Data can be consolidated auto- matically into reports for storage and analysis by higher-level applications running in the cloud. By facilitating set up, the S-Tool
utility helps manage materials that could deteriorate over time. Automat- ically monitoring stock age and con- dition, for example by observing time limitations on moisture-sensitive de- vices (MSDs) and checking use-by dates of components or solder paste, helps prevent out-of-date or unsuit- able materials from being incorporat- ed into finished products. A compo- nent tower storage system, connected with the mounter’s parts-remaining
See at APEX, Booth 2921
Data collected in real time and stored in the traceability database can support activities that range from customer relations to equipment maintenance or product design.
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counter, helps minimize stoppages for reel and feeder changes and enables continuous opera- tion if used to coordinate tape splicing. The system records data that includes
board code, solder paste type and the identi- ties of component feeders and reels, all of which can be collected by a handheld barcode reader. A typical example might be recording barcode information such as brightness (BIN), color temperature and illumination pattern of LEDs to block components with dissimilar characteristics from being used in the same assembly. The T-Tool supports traceability by
recording each individual assembly identifier with its associated board identity and compo- nent data for every placement on the board. This is one area where the underlying data structure of the SMT equipment is critical for
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