Global industries are buckling under a semiconductor shortage—and unlike other shortages either directly or indirectly caused by the COVID-19 pandemic, the semiconductor bottleneck has staying power. Chip supplies are expected to be thin on the ground well into 2022, a supply constraint that multiple factors have caused:
- At the start of the pandemic, auto manufacturers scaled back their semiconductor orders due to slackening demand.
- The demand for consumer electronics increased at that same time.
- Automotive demand came back stronger and faster than expected.
- Now both consumer electronics companies and auto manufacturers are competing over a limited semiconductor supply.
A fire at an auto-chip foundry in Tokyo compounded these shortages and production slowdowns due to widespread power outages in Texas and droughts affecting plants that often use over 40 million gallons of water per day.
Speeding Up Semiconductor Production Means More Than Hitting a Switch
Semiconductor manufacturing is an immensely complex process that involves manipulating systems at the atomic level. As a result, the average semiconductor can take up to 26 weeks to create. You can assume that every semiconductor foundry on the planet operates flat out to meet demand, but accelerating these complex processes isn’t simple. Also, there’s a real risk that speeding up semiconductor production can lead to undesirable results.
Let’s look at the Tokyo fire as one example. This incident stemmed from an electrical fault inside just a single piece of equipment. There’s nothing to suggest that this fire was caused by undue haste. Still, it’s easy to imagine scenarios where heightened production schedules force an organization to skimp on maintenance, resulting in damage to capital equipment.
Also, semiconductor manufacturing facilities may not have the technology or expertise to detect and mitigate equipment issues before they cause problems. It’s ironic, but although semiconductor foundries handle the vast boom in Internet of Things technology that has powered Industry 4.0, semiconductor foundries have yet to adopt this technology for themselves.
Using QMS to Add Smart Manufacturing to Semiconductor Foundries
A recent report from Siemens suggests that many, if not most, semiconductor foundries must use manufacturing execution systems (MES) over ten years old. These legacy software systems place bottlenecks on productivity. They force technicians to shuttle between terminals to input data manually, which wastes productivity. Capacity planners don’t have real-time intelligence regarding their productive capabilities, which means they often set unrealistic goals. Last, engineers have no easy way to aggregate data from different systems. They need to pull and compare reports manually to receive information from across the manufacturing lifecycle.
That might not seem like the best news for semiconductor foundries, but it reveals that there may be more slack in semiconductor manufacturing processes than previously suspected. With a relatively small investment in sensor technology and quality management systems, semiconductor foundries have the potential to speed their production while mitigating risks significantly.
Using Automation to Remove Productivity Bottlenecks
When technicians have to copy information between different systems manually, it takes time and increases the potential for error. QMS can sit between these different systems, provide integrations, and act as a single source of truth. In other words, when a technician updates one system, that information passes through the QMS automatically and into the records for every other connected application.
Using Analytics to Improve Capacity Planning
When acting as a single source of truth, QMS can capture production data from across the entire organization—and then perform analytics on that data. That gives capacity planners the ability to create more accurate forecasts regarding future production. By connecting to vendors and suppliers, the QMS can help planners incorporate data regarding material availability and new process improvements, refining their predictions even further.
Aggregating Data Across Production Cycles to Improve Processes and Productivity
Last, engineers can collect production data from capital equipment and aggregate it into a single dashboard. That strategy makes it much easier to understand the semiconductor manufacturing process from a holistic standpoint, from testing to design. Once understood, it’s much easier to optimize design, maintenance, testing, and production processes to speed productivity.
Collectively, these improvements in smart manufacturing can significantly enhance productivity in the semiconductor manufacturing industry. For example, it’s easy to imagine a scenario where the foundry speeds up its production line while relying on instrumentation to check for out-of-band readings among its capital equipment. By doing this, the foundry can forgo its routine maintenance schedule and instead conduct inspections and repairs only when necessary, which can diminish the impact of unplanned downtime.
Potentially, semiconductor foundries could also QMS to optimize water usage, refine their raw materials usage, improve inspection schedules, and conduct failure mode and effects analysis to avoid potential consequences of increasing production schedules. They can also use document control applications to collect information and respond to internal and external audits if a failure ever occurs.
At ETQ, we work closely with some of the most regulated industries in the world to help them create products quickly and safely. Reliance NXG, our flagship QMS, helps improve processes across the entire product lifecycle, resulting in increased revenue and happier customers. Request a demo today and learn how QMS can enable faster, smarter manufacturing in your industry.