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SMT007-July2019

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JULY 2019 I SMT007 MAGAZINE 119 Semiconductor The development and deployment of tech- nologies for data flow are accelerating while data analytics and data retention protocols are increasing at a faster rate than first anticipated. It is critical to collect the crucial data as well as establish guidelines to perform intelligent anal- ysis and exercise the appropriate algorithms to specify data-driven decisions. Several topics related to data are under consideration: • General Protocols 1. "All" versus "anomaly" data retention practices 2. Optimization of data storage volumes 3. Data format guidelines for analytics to drive reactive and predictive technologies 4. Data quality protocols enabling improve- ments in time synchronization, compression/uncompression, and blending/merging 5. Guidelines to optimize data collecting, transferring, storing, and analyzing • Data Considerations for Equipment 1. Defining context data sets for equipment visibility 2. Improving data accessibility to support functions, such as advanced process control 3. Data-enabled transition from reactive to predictive functionality 4. Data visibility of equipment information (state, health, etc.) Outsourced Semiconductor Assembly and Test (OSAT) The key attribute needs for data flow being considered by OSATs include: • Are the requirements for data flow within the OSAT vertical different from those required between the verticals (semicon- ductor-to-OSAT or OSAT-to-PCBA)? • Are security requirements for vertical data flow and horizontal data flow similar or different? • Are the requirements for data flow between being dependent on edge, fog, and cloud on security requirements? • Are the data flow needs different for an OSAT managing high product mix that are competitive in nature versus an OSAT managing low product mix? • What are the criteria to determine the value of the cloud at different levels of data flow architecture maturity/deployment? • If there is a high level of cloud adoption for the ERP, does this drive adoption at machine-level data flow to the cloud? Printed Circuit Board Assembly (PCBA) Subject matter experts agree that access to data will be ubiquitous, cross-platform, and on-demand. Data flow will leverage technologies like augmented reality to help survey produc- tion floors for imminent issues, and machine communications will proactively identify and diagnose issues before an instance. The manage- ment of the type of data and assurance that the recipients receive the "appropriate" volume of data is critical. Collaborative Efforts The smart manufacturing chapter identified several critical gaps that must be addressed to realize the benefits of smart manufactur- ing and Industry 4.0. Based on the informa- tion gathered during the preparation of the chapter, iNEMI is organizing an initial smart manufacturing collaborative project to address back-end electronic packaging commonality. This project plans to address the cost and inefficiency of unique customization require- ments across the packaging back-end, seek- ing to demonstrate the benefits of back-end commonality by defining key cases/examples (e.g., tray carriers) to address both physical and digital (information) commonality. This project plans to analyze and quantify the bene- fits of improved cycle time, utilization, yield, costs, etc., in a smart manufacturing environ- ment. For additional information, contact info- help@inemi.org. About iNEMI The International Electronics Manufactur- ing Initiative (iNEMI) is a not-for-profit, highly efficient R&D consortium of approximately

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