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The Advantages of Self-Teaching into the Automated Device Programming Process

The Advantages of Self-Teaching into the Automated Device Programming Process

Modern Automated Programming Systems (APS) are expected to handle hundreds of different packages while maintaining high uptime, high first-pass-yield and near 100% quality.  At the same time, package proliferation, the trend towards shrinking devices and the need to set up multiple jobs per shift has placed more emphasis on the need for skilled operators to set-up and teach new jobs.

In many markets, job lot sizes can be relatively small, from a few hundred to a few thousand devices.  Programming times vary based on file sizes and impact the effective production rate of the APS.  With typical production run-rates of 1,000 devices per hour, it is easy to see that efficient job set-up is critical to machine utilization and real production output per shift. Small chip-scale packages and device pitch as small as 0.35mm push the capability of many APS solutions and make job setup challenging, even for skilled operators. If pick and place teach locations are incorrect, highly repeatable automated machines will effectively reproduce those human-induced teach errors, leading to quality issues or defects. Latent failures are particularly important to all manufacturers because it diminishes the reliability and value of end products, leading to even more severe failures and higher support costs downstream.

Using teaching methods where the operator has to manually pick and place devices for each socket teach location, then guide the automated machine to manually teach the critical z-height of the device in-socket through human observation is cumbersome, time-consuming and potentially inaccurate.  Job set-ups using this traditional manual process can take 30 minutes to an hour or more when socket count is high, decreasing valuable production time. The solution is to use automated self-teaching for each job.

A Better Set-Up Process

With fully-automated self-teaching, operator involvement in the job set-up process is greatly reduced. The initial job set-up of input/out locations and peripherals is familiar. Blank devices in media (tape, tray, tube) are loaded and Input/Output peripheral locations are taught.  From that point, the process becomes radically different and more productive. The operator simply places a blank device in Site1, Socket A and executes a command to begin the auto-teaching process. This is the only time the operator is required to manually place a device in-socket. Next, the pick head moves to the initial Socket A location. The nozzle then moves down and automatically detects the top of the device in the socket, accurate to within 15 microns.  Now that the initial device and z-height have been taught, the machine subsequently picks devices from the input location and teaches sockets and sites “1-n” respectively. As each site is taught, the programming operation begins immediately without operator intervention until the APS is at full production capacity. In effect, the operator places one device in-socket, pushes a button and the machine teaches and begins the programming job, in parallel. The operator is then available to complete other important duties such as staging, logistics, and planning. System self-teaching is a clearly superior approach to automated device programming.

Fully-automated Teach saves time and ensures quality

The positive financial impact of self-teaching can be substantial.  Saving 15 minutes or more per job is quite feasible and even understated for systems with dozens of programming sockets.  From the table below, you can see that for a factory with 3 shifts and 3 job setups per shift, saving as little as 15 minutes per setup can make an impact in terms of both hourly savings and additional production capacity.   In our example, that equates to over $33,750 USD and 563 hours of gained productivity annually.  Assuming 1,000 DPH as a typical production run-rate, the operation can produce additional 563,000 devices per year. The financial impact over a five-year amortization schedule really clarifies the value of self-teaching; with the potential to generate $168,750 USD.

Summary

Modern automated programming operations are expected to achieve high equipment utilization, near-perfect quality, and the lowest possible programming cost per device.  Implementing self-teaching into the automated programming process should be considered as a game-changing solution to improve each of these important metrics.


Self-Teaching – by the Numbers

New job teaches per shift 1 2 3 4
Working days per year 250 250 250 250
Shifts 3 3 3 3
Factory burden rate per hour $60.00 $60.00 $60.00 $60.00
Hours saved per setup 0.25 0.25 0.25 0.25
Hours saved annually 188 375 563 750
Annual savings $11,250 $22,500 $33,750 $45,000
Job Changes per Shift
Amortization Years: 5 Year 1 Year 2 Year 3 Year 4
Shift 1 $18,750.00 $37,500.00 $56,250.00 $75,000.00
Shift 2 $37,500.00 $75,000.00 $112,500.00 $150,000.00
Shift 3 $56,250.00 $112,500.00 $168,750.00 $225,000.00
Shift 4 $75,000.00 $150,000.00 $225,000.00 $300,000.00
CSP Device Programming Strategies for the C-Suite

CSP Device Programming Strategies for the C-Suite

By Srivatsan Mani, former Director of Engineering, BPM Microsystems, Inc.
Originally published in Vol. 18, No. 2 of Global SMT & Packaging Magazine

Good things come in small packages, but small packages can be tricky and costly to handle. The trend for higher density devices and smaller package sizes creates a unique set of challenges for the programming centers and manufacturers programming those devices. A light puff of air sends small parts flying, and misalignment of less than .2mm creates placement issues. This article shares best practices decision makers should consider when purchasing or upgrading production equipment to program small IC devices to maximize speed, quality and cost savings. 

The rise in demand for small device packages

Mobile phones, PDAs, and other mobile products continue to take on new roles such as digital camera, video camera, and TV receiver. These functions require an increased number and greater variety of semiconductors in order to operate, while consumers want their finished products in ever-smaller form factors. Thus, as mobile phone sales have soared, demand for the chip-scale package (CSP) has increased faster than any other IC package type over the past decade or so. The demand for smaller packages with higher densities affects other segments including automotive, industrial, medical device and Internet-of-Things. As the need for complex electrical circuits increases, programmed devices are developed in smaller and smaller packages to free up much-needed space in circuit design. As a result, programming centers and manufacturers are moving towards purchasing or retrofitting existing pick and place machines that are capable of programming such devices with little or no device failures.

Manufacturer challenges handling small devices

Pick and place errors account for the majority of quality issues when programming small devices. Pick and place inaccuracy occurs when the machine is not taught precisely or is inaccurately placing parts due to unaccounted longer x-y axis settling times before a place. Teaching the z-height for a machine manually is nearly impossible for small devices, and for larger devices, operator skill and experience are required. Programming centers and manufacturers incur added costs for labor, machine idle time, lost devices, damaged devices, escapes, and poor yield.

Process control improvements

Automated IC device programmers lift and move devices using a vacuum nozzle attached to a robotic machine to perform repetitive operations. The negative pressure lifts the object and holds it against the nozzle while moving it to the desired location and then setting it into place. However, very small objects, such as small computer or digital chips, including Wafer Level Chip Scale Packaging (WLCSP), small-outline transistors (SOT), and dual-flat no-leads (DFN), may be lifted by the nozzle prior to contact by the nozzle with the object. The vacuum may cause the object to “jump” up to the nozzle.

Operators using process control software teach the robotic machine the height of the object before it begins repetitive production operations. When setting up a job, operators use the process control software to teach the robotic machine the location (x, y, and z) of the input media, output media, peripherals, and programming site and socket. To teach z-height, the operator depresses the nozzle on the handler until it just touches the device. With IC device packages getting smaller, reaching .305mm thick and sizes of 1.7mm x 1.4mm, manually teaching the z-height of the device into the socket is nearly impossible. An operator cannot clearly see deep into the socket to see when the nozzle touches the device. With a flashlight and the assistance of a co-worker, multiple attempts and adjustments occur to determine the z-height.

During a teach cycle, the jump by the device causes the height to be measured incorrectly by the robotic machine that moves the nozzle. Subsequently, during repetitive operations, this incorrect height causes the machine to attempt to pick up the object before making contact. This leads to pick and place errors, dropped parts, cracked parts, and continuity errors. If alignment is off by even .2mm, the teach process must be repeated to avoid cracking or otherwise damaging the device.

Customers report manual teaching small devices takes up to 30 minutes per station. For programming centers with five changeovers per day, this costs 2.5 hours machine idle time plus the costs of labor and lost or damaged devices. Programming centers and manufacturers should consider process control software and equipment with automated teaching capabilities for small parts. For example, BPM Microsystems WhisperTeach™ automates the task for the operator. It completes the task in 4.37 minutes with a standard deviation of 0.5mils, resulting in a savings of up to 25.63 minutes per station or 2.14 hours per day with five changeovers per day.

Accurately taught jobs improve yield by eliminating pick or place errors. Customers have reported yields as poor as 80% on very small parts using manual teach depending on operator skill. Process control software with automated z-height teaching produces a job yield of 99.99% by eliminating any teach related issues.

Production control efficiencies

After completing the job setup and production begins, the accuracy of placement is critical to avoid damaging the device. Manufacturers need to ensure their systems self-calibrate z-height during production to eliminate the need for manual adjustments to compensate for variations in atmospheric pressure, nozzle size, flow rates, filter conditions, and more. This self-calibration by the machine ensures accurate handling throughout the job. In addition to an intelligent process control software and pneumatics systems, look for systems equipped with a high-quality vision system to ensure proper alignment of small parts before placement at each station. When integrated with the production software, vision systems allow the machine to align the device while in motion at high speeds.

For small parts, placement accuracy can be a challenge for systems that are unable to settle their x-y motion fast enough. Look for systems with designs allowing them to operate at maximum throughput without having to slow down the system to handle small parts. Customers achieve faster throughput and better reliability with a well-designed motion system.

3D inspection to increase the quality

■ Precise Laser Micromark Measuring .1mm x .1mm.

Manufacturers looking to reduce scrap monitor each stage of the manufacturing process and take corrective action early. Device programming systems equipped with 3D inspection systems identify damaged parts early in the process. This allows manufacturers to take quick corrective action, resulting in higher quality, minimized reflow and lower overall costs.

3D inspection systems provide full device package validation after programming. High-performance systems support the verification of a variety of device packages including BGA, CSP, QFP, TSOP, SOIC, and J-Lead devices. When looking for an inspection system, features should include measurements for coplanarity, bent lead, pitch, width, diameter, standoff and XY errors.

Inspecting the coplanarity on leaded devices, such as the SOT-23 that measures 2.2mm x 2.7mm, ensures you do not exceed the manufacturer tolerance, which can create long-term reliability concerns of the device. The stress from bent leads may cause cracks in the package, reducing resistance against moisture and consequently present failure in the field due to internal corrosion. 3D inspection systems also identify devices with defective or missing balls on a BGA. By recognizing and removing damaged devices before final placement, manufacturers can prevent quality issues that would otherwise escape. This, in turn, improves production yield and process stability.

Laser marking for traceability

Manufacturers must thoroughly implement traceability control to maintain and confirm quality. Marking a device with a serial number, for example, enables traceability to the programming system, the site and even the socket that programmed the device.

Smaller, thinner devices require fine control of the laser power to avoid damaging the device. Additionally, smaller devices require and higher resolution marking capabilities. When purchasing a laser for your device programming system, look for a hybrid laser system that combines fiber and Nd:YAG laser technologies for precision marketing quality. Micromarking information in a limited space requires ultra-fine marketing capabilities, which is impossible with conventional laser marketing systems. Hybrid laser marking utilizes fine laser setting control, resulting in shallower marks, vivid coloration and a lower thermal impact.

By recognizing and removing damaged devices before final placement, manufacturers can prevent quality issues that would otherwise escape. This, in turn, improves production yield and process stability.

A laser with a power monitor control provides high precision calibration of the laser mark, allowing accurate measure and control of laser energy output. The ability to monitor and control the laser power avoids damage to the device and reduces scrap. In electronics manufacturing, device damage affects quality, reliability, and profitability. A hybrid laser is an optimal solution for small device marking applications where it is necessary to eliminate the effect of heat transfer and control the maximum penetration depth while also providing high-contrast micromarking.

Conclusion

Modern electronic products favor higher density devices in smaller package sizes. Manufacturers and programming centers are purchasing or upgrading existing IC device programming systems to support the demands of programming small devices. A unique set of challenges exist to pick the small device out of tape, place it in the socket, program the device, laser mark the device, inspect the device through 3D inspection, and then place it out to tape. All of this needs to happen quickly, efficiently and with high quality. Decision makers need to consider many requirements when selecting an IC device programming system capable of handling small parts. Ensure the process control software and pneumatic system are qualified for small part handling and automatically teach z-height. Look for a self-calibrating machine with a high-performance vision system capable of aligning devices at high speed, on-the-fly, during production to maximize DPH. Systems with well-designed motion systems achieve faster throughput and higher reliability. Invest in a hybrid laser with power monitoring controls and micromarking capabilities to ensure device traceability. Finally, select a 3D inspection system that performs full device validation after programming, including checks for bent leads and defective balls, for quality and lower overall costs. Following these strategies will ensure your IC device programming system handles small devices with the speed, quality and overall cost savings required for modern electronics manufacturing.

Link to original article

Originally published in the February 2018 edition of Global SMT & Packaging 

SRIVATSAN MANI

SRIVATSAN MANI

Former Director of Engineering

Srivatsan Mani was the Director of Engineering who works with electronics manufacturers and programming centers to innovate solutions that modernize and improve their businesses. With more than 16 years of experience working with device programming systems, process control software, and device programming technology at BPM Microsystems, Inc., Srivatsan knows how to leverage technology to speed up the process while producing higher quality products at lower overall costs. Srivatsan led the development of the award-winning VectorEngine™ site programming technology, patent-pending WhisperTeach™ automated z-height teaching solution, and BPWin™ process control software. Srivatsan holds a degree in electronics and communication engineering and masters in computer systems engineering.

Mastering eMMC Device Programming

Mastering eMMC Device Programming

How to Maximize Speed, Quality and Cost Savings

Abstract

Exceptional products start with exceptional programming. Mass programming is one of the important stages in final product build and release.

This white paper shares information to help engineers involved in the industry of eMMC device programming. It summaries the basic specification that all eMMC devices follow including device architecture, bus protocols, modes, data read/write, and production state awareness.

The white paper also lists the criteria decision makers should consider when evaluating the effectiveness of their Universal Programming equipment. The quality and efficiency of programming equipment affect the quality and cost of the final product as well as time to market.

Introduction

Over the past decade, the demand for high-density, nonvolatile memories with a small footprint has increased dramatically. Two of the most popular markets driving this demand are handheld devices and automotive. Demand for handheld devices continues to drive the research for high-density, low power, low-cost, high-speed, nonvolatile memories while maintaining the small footprint. NAND-type flash memory is the perfect match for such a market. The increased consumer demand for high-tech features in automobiles, such as infotainment systems, is also a big driver of demand for high-density NAND-based devices.

Flash memory is a solid-state, nonvolatile storage medium that can be electrically erased and reprogrammed. There are two types of flash memory, NAND and NOR, named after the NAND and NOR logic gates. NAND flash memory was introduced by Toshiba scientists in 1987 [1] and can be written and read in blocks. NAND flash memory was not fully utilized until recently due to its low reliability. Early NAND flash experienced bit flips, the possibility that some programmed bits read back as zero while previously programmed bits read as one, or vice versa. Bit flips introduced bad blocks over the service life of the device. With the advances in research in Error Correction Codes (ECC) [2][6][7], along with implementing new Bad Block Management (BBM) schemes [3][7], engineers were able to better detect and correct bit flips. This increased the appeal of NAND flash memory and allowed it to dominate over its more-expensive rival, NOR flash memory.

The inevitable use of ECC and BBM schemes with “RAW” NAND devices lead to increased complexity when handling these devices. To avoid such difficulties, and reduce the design and time to market cost, the trend shifted to the use of “managed NAND devices”. The typical architecture of any managed NAND device includes a raw NAND memory, which is the main storage media, plus a microcontroller [5]. The microcontroller acts as the interface between the host and the raw NAND memory. It does all management tasks such as bad block management, error detection, and correction, wear leveling, and more. This helps hide the complexity of these heavy lifting tasks and frees the host (and the hence the designer) to focus on application-specific tasks. Furthermore, both customers and programming houses do not need to research and provide details (and sometimes example codes) for specific ECC or BBM schemes. These are many times not easy to obtain and are IP protected. Examples of managed NAND devices include Solid State Drives (SSD), Universal Flash Storage (UFS), Secure Digital (SD) cards, and Embedded Multimedia Card (eMMC) devices.

The focus of this paper is on eMMC devices. It begins with a brief overview of the eMMC device architecture, followed by sections explaining different protocols, speed modes and write modes supported by these devices. A section discusses the new specifications and “production state awareness” feature introduced in recent JEDEC specifications version 5.0 and later. The paper concludes with the top five tips programming centers and decision makers should consider when purchasing high-quality programmers for programming eMMC devices.

Download entire Whitepaper PDF Here

BPM Microsystems Releases White Paper on Device-Driven Serialization

HOUSTON, TX–June 3, 2013– BPM Microsystems, a leading supplier of device programming systems, announces the release of its latest white paper, titled “Advanced Device Serialization Using an External Serialization Server,” written by software engineering manager Nader Shehad. This white paper explains how modern serialization applications can use a more sophisticated approach to facilitate device programming with Device-Driven Serialization (DDS).

DDS is a communication framework that allows the External Serialization Server (ESS) to communicate bi-directionally with a device-specific programming algorithm running as part of the programming application. This allows the ESS to become part of the programming algorithm and extends the functionality of typical serialization techniques.

“The bi-directional communication framework provided by DDS allows greater flexibility in the External Serialization Server,” said Shehad.  “For instance, the ESS can read device-specific data for logging purposes, control details about the programming operation, and be notified each time the device is powered on or off.  Moreover, a detailed failure analysis can be provided to the ESS to indicate exactly which phase of the program and/or verify operations failed. The ESS could then store this information in a database, send it via e-mail to key personnel, or integrate with other customer systems.”

DDS is a breakthrough in the serialization process that addresses today’s complex requirements of modern serialization. To find out more about Device-Driven Serialization, download the complimentary white paper here

About BPM Microsystems
Established in 1985, BPM Microsystems is a global supplier of electronic device programmers for all applications. The company is the leading supplier of vision-based automated programming systems and sets the standard in device support, performance, ease-of-use, and cost-of-ownership. The company offers a wide variety of device programmers including Universal Programmers, Concurrent Programming Systems® and Fine-Pitch Automated Programming Systems.

BPM Microsystems’ financial statements are audited by Pannell Kerr Forster.

Overview

In the device programming industry, serialization is the process of writing unique data to each programmed device. It can be used to program basic numeric serial numbers to a single device address and can also be used to program more complex data such as MAC addresses, encryption keys, GUIDs and randomization seeds to several device addresses on each device…