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Far beyond standard quality verification

The quest for real-time statistical process control with automated optical inspection
Far beyond standard quality verification

Many quality-conscious electronics manufacturers have integrated automated optical in-spection into their production lines. The emphasis has been placed on achieving a higher level of assembly verification to identify defects and to improve yields. AOI is able to gen-erate a tremendous amount of additional useful data. But how can that data be used?

Dr. George Ayoub, Machine Vision Products

Throughout electronics manufacturing, SPC has been implemented with some success. Quality has improved in many cases, and the level of accountability has risen as data, some of which is collected by AOI systems, is on hand to monitor defects and indicate less than optimum system performance. Simply stated, SPC is amethod of monitoring, controlling and improving a process through statistical analysis. Its four basic steps include measuring the process, eliminating variances in the process to make it consistent, monitoring the process, and improving the process to its best target value.
Entering statistical process control (SPC)
There is, however, an inherent flaw in the general use of SPC: the data is not real time. Typically, data is analysed, line problems are discovered, and changes are then made – but this process is hours and sometimes days after the fact. During the time gap between identifying the fault and correcting it, thousands of imperfect boards may have been produced, money has been spent and scrap levels have risen. In an environment of tight profit margins, where getting it right the first time is critical to the health of manufacturers’ bottom line, it is simply not acceptable to waste time and resources producing faulty boards or operating sophisticated SMT lines inefficiently, respectively.
SPC would be real-time only in a perfect world. But how would real-time SPC work? Ideally, when a process deviates from a pre-set specification, the operator would immediately be notified of the defect, of its cause and a plan of action suggested to instantly correct it. The fault would not be something identified the following morning at the daily SPC meeting. The key to real-time is the coupling of sophisticated AOI and SPC methodology, using traditional inspection information asa key tool for SPC on the line. The outcome ishigher throughput and yield, greater line efficiency and lower overall manufacturing cost.
Linking AOI and SPC through CIMCIS
Using the standard defect data and variablemeasurements that sophisticated AOI systems can generate, it is possible to create a real-time sys-tem that alerts operators whenever any process exceeds pre-set limits – and does so immediately. This is, in essence, real-time SPC, a system that continually monitors line performance, detects problems with each board, measures pick-and-place, feeder and nozzle performances, and stringently controls process variability to opti-mise performance, throughput, first pass yield and overall quality.
The two keys to such a system are fast, accurate AOI, linked to a series of line controllers, and an intelligent network that maintains AOI data and quickly translates the board reference data into specific machine, feeder and nozzle information. At Machine Vision Products (MVP), we’ve developed a system that links our AutoInspector series of AOI systems to CIMCIS. This is a fully scale-able, plug&play hardware/software configuration, which uses standard AOI information to monitor and dramatically improve the performance of SMT production lines. Critically, because the AOI systems can take measurements from anywhere on the line – including paste, pre-reflow and post-reflow/wave – the CIMCIS Expert Response Sys-tem can identify problems created by individual placement machines, feeders and nozzles, and send operator instructions and corrective actions to the ”guilty” equipment, based upon the process control limits set by engineering.
The core CIMCIS Machine Manager Terminal collects and stores production information and automatically calculates Semi E-10 metrics. Of particular interest are the best and average cycle times, run, blocked, starved and down times and the top-10 feeder and nozzle problems. The CIMCIS Line Controller and Data Server uses an RS-485 network to collect data. The network allows the transfer of data from the stencil printer, the pick&place machine, the reflow oven and theAOI system. The real-time SMT performance, quality and production data is stored in a centralSQL database in an open (ASCII) format withlocal resiliency provided by the NT workstation database.
The result of this configuraton is something we’ve termed dynamic process control – because in operation it goes beyond real-time SPC – add-ing audible alerts and, via a visual display panel, proactively suggesting to the operator what corrective actions should be taken. The key is that dynamic process control is immediate, proactive and transparent to the user. There is no need to know about control charts and procedures – the sample interface on the machine uniformly displays on all machines. Dynamic process control is not theoretical. It is already in place monitoring production lines. Not only is it used to detect and quickly correct errors; this system is also being employed for improved quality control, real-time line balancing, inventory control and production forecasting.
What dynamic process control accomplishes
The combination of CIMCIS technology coupled with MVP’s flexible AOI capabilities can be used for a variety of critical analyses. By calculating best and average cycle times, users can know, often for the first time, just how much system utilisation is actually being achieved. It’s not uncommon for operators to believe that their lines are reaching upwards of 75% utilisation, but without real-time data to substantiate this belief. In many cases, the addition of such a system has brought good and bad news. The bad news is that utilisation has often been much less than 75%. The good news is that it has immediately found faults, suggested corrective action and quickly helped to return lines to full utilisation.
It’s not unusual for the addition of dynamic process control to dramatically improve pick& place utilisation any-where from 5% to 70%. In one large facility, performance of Fuji machines was improved by 71%, and Universal placement machines were improved by 34%. Dynamic process control data can also be used to track faulty nozzles and feeders back to the manufacturer, track faulty components to a specific reel, and quickly optimize the line to meet a changing product mix – an invaluable tool for many users.
More CIMCI mod-ules have been developed to perform other real-time tasks. These are used for example: setup verification to eliminate misleads by validating parts numbers for each reel load; works in progress tracking to log the progress of panels through the process; materials traceability which allows users to trace field faults back to a particular component from a specific manufacturer; material management to track consumption and warn of impending shortages; and in-spection feedback provides a loop between AOI systems and placement machines that alerts operators to potential feeder problems. In addition, the system can be used to verify line setup, helping cus-tomers build products right the first time, without the need for expensive repairs and increased operational costs.
Finally, in the age of digital information and wireless communications, the ad-dition of a web browser to the dynamic process control system allows remote access (firewalled and with NT security) to all information, and provides users with the capability to alter line parameters in order to improve performance. The sys-tem utilizes a standard SQL database running on an NT4 server. Data is stored in an open ASCII format. The staff is able to easily run simple reports utilizing standard tools. Data can also be integrated into a customer’s own standard information collection and reporting system.
From real-time SP to dynamic control
Combining AOI data with unique software and data collection modules placed throughout an SMT production line is turning static SPC into real-time dynamic process control. The gathering of data is transparent, and all system warnings are driven by pre-set limits. Specific corrective actions are recommended with instructions flashed on the data collection mo-dules. Systems can bedrilled down to specific machines, nozzles and feeders – and this access can be accomplished from any on-line computer anywhere in the world.
Although dynamic control can function as a real-time ”report card,” showing how well lines and machines are running and delivering the data to prove it, it is not about finding faults. Rather, combining AOI with hardware and software to gather and analyse data be-comes an-other tool in the quest for optimum quality and the best possible line performance. Given the need to speed time-to-market and the economic necessity of building assemblies right the first time, standard AOI and SPC can no longer provide the full range of information (down-time, up-time, delay-time, just to name a few) need-ed to opti-mize line performance and guarantee quality levels, much less do so in real-time.
Not so long ago, before the almost universal adoption of AOI and SPC by board assemblers, quality levels and line optimization were merely ”guesses”, – based on ”anecdotal” evidence and after-the-fact field fail-ures. With AOI, defect detection became much more precise. Manufacturers could, for the first time, ”see” a vital problem in real-time. With the use of SPC methods, line optimization and quality control were improved. And for the first time, engineering had hard data that could be used to monitor the line and adjust it for optimal performance – albeit after the fact.
ZUSAMMENFASSUNG
Statistische Prozeßkontrolle (SPC) ist eine bewährte Technik, um Baugruppenfertigungen zu überwachen und Abweichungen zu korrigieren. Doch sind Korrekturen nur dann optimal, wenn sie umgehend auf Basis von ständig verfügbaren Echtzeitdaten erfolgen und nicht auf älteren Trendaussagen. Die Verbindung des AOI-Systems über ein spezielles Netzwerk mit diversen Kontrolleinrichtungen am Fertigungsequipment sorgt für die umgehende Verfügbarkeit ”lebender” Prozeßdaten und damit im Bedarfsfall sofort für gezielte Aktionen.
RÉSUMÉ
Le contrôle statistique des processus (SPC) est une technique qui a fait ses preuves dans la surveillance de la fabrication de modules et la correction des écarts. Mais les corrections ne sont parfois optimales que si elles se font entièrement sur la base de données en temps réel et non pas en fonction de tendances remontant à plusieurs jours. La connexion du système AOI avec divers équipements de contrôle via un réseau spécial assure la totale disponibilité de données actuelles des processus.
SOMMARIO
Il controllo statistico di processo (SPC) è una tecnica affermata per sorvegliare la produzione di gruppi costruttivi e per correggere eventuali scarti o scostamenti dalla norma. Tali correzioni si rivelano ottimali solamente se esse avvengono all’istante e sulla base di dati rilevati in tempo reale e non di trend rilevati giorni addietro. Il collegamento delsistema AOI con diversi dispositivi di controlloattraverso una speciale rete telematica permetteal sistema di disporre immediatamente di dati di processo „ancora vivi“.
Current Issue
Titelbild EPP EUROPE Electronics Production and Test 11
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11.2023
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