Semiconductors are among the most crucial electronic components. As such, ensuring smooth semiconductor logistics — both upstream and downstream — is vital.
Any delays, inventory issues, product loss or other disruptions will create significant waves throughout the supply chain. Consider how the Covid-era chip shortage led to a production drop of 7.7 million vehicles and lost revenues of $210 billion.
Advanced logistics solutions let organizations prevent and mitigate similar challenges in the future. Here’s how.
Ensuring availability
The most important role of logistics in semiconductor manufacturing is to ensure a steady stream of materials and, consequently, outgoing products. Internet of Things (IoT) tracking systems help by providing needed visibility into the supply chain.
Credit: Bernd Dittrich
IoT trackers can provide real-time information on a shipment’s origin, location and physical condition. Seeing such data means manufacturers can ensure incoming materials arrive on time and in good shape. It also offers early warnings if something goes wrong, giving them room to adapt to avoid the worst impacts of a material shortage or delayed delivery.
Companies that gathered and consolidated such data into digital dashboards were twice as likely to avoid supply chain disruptions in 2022 as their competitors. The same tools can offer similar assurance and adaptability to downstream partners to minimize ripple effects.
Maximizing efficiency
Along those same lines, advanced semiconductor logistics enables higher operational efficiency. Real-time visibility informs better inventory management practices, letting manufacturers increase safety stocks when necessary or adjust production to minimize delays amid disruption. Over time, this data can also reveal broader changes that may yield improvements.
Building a digital twin of the supply chain shows organizations optimization opportunities they may miss otherwise. For example, alternative transportation solutions may add efficiency. A heavy-haul trailer can carry 80,000 pounds of material — more than enough for semiconductor production — and could be available where semitrucks and drivers are in short supply. Analyzing a digital twin with artificial intelligence (AI) could reveal when this strategy would shorten last-mile delivery timelines, leading to higher efficiency.
Automation is another key technology here. Automated material handling can move products through a warehouse and load trucks faster than manual processes. They also reduce injury risks, avoiding accident-related downtime so logistics workflows can speed up with less disruption.
Minimizing costs
While innovations like these entail higher upfront costs, they often reduce spending in the long run. Such long-term savings are crucial for the electronics industry, given how semiconductor prices have risen since late 2021 after a steady decline over the previous decade.
Much of advanced logistics’ savings stem from efficiency. Higher output in the same amount of time results in lower production costs per semiconductor. Similarly, automation minimizes material handling mistakes and record-keeping errors to prevent unnecessary expenditures from rework, downtime and miscommunication with 3PLs.
The IoT is particularly valuable for this goal. IoT equipment sensors can reduce repair costs through predictive maintenance, alerting workers to emerging issues to prevent vehicle breakdowns. Smart sensors can also produce enough data to reveal the least efficient routes or practices, informing more cost-effective strategic planning.
Protecting parts and products in transit
Optimized logistics in semiconductor manufacturing also prevent material and product losses. Supply chains are long and complex, so damage in transit is all too likely in many cases. AI route planning software and IoT tracking provide the agility and insight necessary to minimize this risk.
Credit: Chuttersnap
Machine learning can identify hazards like long shipping times or extreme weather conditions that may threaten incoming shipments. Semiconductor producers can then reroute deliveries to avoid such threats and ensure their raw materials arrive usable. As a result, they prevent losses and can maintain production levels.
Once semiconductors ship out, IoT sensors can monitor temperatures, humidity and physical shocks within their packaging. Alerting stakeholders when factors fall outside acceptable parameters enables quick route changes or other adjustments to keep chips in good condition. Considering how sensitive these components are, that assurance goes a long way.
Reducing carbon footprints
Advanced logistics also plays a role in making the semiconductor industry sustainable. Roughly 15 percent of semiconductor lifetime emissions come from the supply chain. Businesses can reduce these figures by embracing AI, automation and the IoT throughout their operations.
AI analysis of digital twins can simulate changes to find optimal strategies for carbon reduction. That may include sourcing from closer suppliers, using a more eco-friendly 3PL, electrifying fleets or a hybrid of multiple approaches. Whatever the case, meaningful improvements are often difficult to find or quantify, so using AI and digital twins reveals fixes organizations may have overlooked.
Real-time data from the IoT supplies the information such algorithms need to make informed predictions. Smart sensors can also reduce emissions by keeping vehicles in top condition through predictive maintenance or automating energy-saving facility operations.
Optimizations within the supply chain have ripple effects across the semiconductor industry. Manufacturers and the businesses depending on them should take note of this opportunity.
Semiconductor logistics practices often have substantial room for improvement. Once organizations recognize this potential, they can capitalize on new technologies to drive positive changes across their value chain.
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