How is Industry 4.0 Transforming the Semiconductor Industry: Applications and Benefits

Owing to the increasing popularity of IoT and AI in semiconductor industry, the expanse of semiconductors has broadened significantly. Today, semiconductor companies need to respond to their customer's needs from the production line to inspection and evaluation systems. IoT in semiconductor companies has a considerable role to play in the field servicing for aspects such as condition-based maintenance. IoT data can also improve the customer experience, increase revenues by creating new aftermarket service offerings, and reduce the cost of service provision.

Connecting IoT data across the spectrum can deliver considerable advantages to the entire ecosystem, and field servicing is a critical component of the value chain.

Smart factories are self-organizing machines enhancing operational profitability and increasing process productivity. The evolution of embedded systems has given rise to a new era of cyber-physical systems (CPS). CPS merges the real and virtual worlds and possesses high flexibility, self-organization, self-adaptability, immense fault tolerance, and risk management capabilities. These attributes consistently improve real-time quality, resource, time-to-market, and cost advantages of the classic production.

Such intelligent systems optimize the in-house production process so that it is not confined to producing a single product but can produce more than one product through multiple remote operators.

Digital technologies go one step further in enhancing product quality. For instance, machine-vision algorithms conduct an automatic quality inspection and quality control using predictive algorithms, relieving constraints in workforce availability while increasing the precision and threshold of quality checks at the semiconductor smart factory. As the SKU count increases for finished products and raw materials, capturing end-to-end traceability becomes the key to getting quality output.

Solutions such as barcode scanners, RFID tracking, and blockchain come in handy to achieve this objective. In the fab, machine learning provides faster and more accurate results in finding and classifying defects in chips.

The high cost of wafers in the semiconductor industry makes it practical to attach electronic components to each wafer carrier or Front Opening Unified Pod (FOUP), ultimately enhancing production efficiency. The data assimilated into the siloed models and analytical software used in Industry 4.0 makes it easier to account for the cost of each item, resulting in better intelligence for business strategy and product pricing.

To reduce production costs and produce more customized batches, automaker OEMs and their suppliers use machine-to-machine (M2M) communications and machine learning-based processes to upend production flexibility.

When deploying Industry 4.0, machines are equipped with sensors to record important events affecting OEE, including production slowdowns or equipment malfunctions. Operators then use a touchscreen interface to enter contextual information, which shortens the time spent on manual data input and provides engineers with in-depth detailing. In the future, Industry 4.0 solutions will take automation a step further by using problem-solving tools to examine machine-log data.

These tools first evaluate historical information and conduct automated data analysis to identify the root cause of problems and then suggest solutions or automatically execute them.

By implementing Industry 4.0, semiconductor manufacturing companies stand to gain in terms of cost leadership as well. As Industry 4.0 spreads its wings across the value chain, any significant cost optimization in the value chain directly impacts the overall cost of semiconductors. While it may seem a costly affair at the start, advanced semiconductor companies will have cost leadership going ahead with their value-added offerings of automated field servicing, improved operational efficiency, and a highly visible supply chain.

According to a McKinsey study, artificial intelligence in semiconductor manufacturing contributes between $5 billion and $8 billion annually to EBIT. This figure could potentially reach between $35 billion and $40 billion within two to three years. Over a longer timeframe of 4-5 years, this figure could rise to $85 billion to $95 billion per year. That amount is equivalent to about 20% of the industry's current annual revenue of $500 billion.

McKinsey's research on semiconductor companies highlighted that a more disciplined approach to lean, combined with the introduction of Industry 4.0 techniques, enables companies to improve labor costs, throughput, and quality.

Besides, through this powerful combination, factories can capture productivity gains of 30% to 50% for direct labor and 10% to 20% for maintenance productivity. There is an average improvement of 10-15 %in overall equipment effectiveness (OEE), increases of 1% to 3% in yield, and a 30% to 50% decrease in customer complaints. The total experience is enhanced multifold by implementing Industry 4.0 in the semiconductor industry.

Industry 4.0 offers enhanced connectivity, enabled by faster and more secure networking. This enhanced interconnectivity through IoT combined with access to real-time data offers manufacturers a holistic view of their value chain, including their customers, partners, and suppliers.