By Charles King, Pund-IT® March 10, 2021
The prestige that technologies enjoy among global businesses and consumers tends to obscure the mundane efforts and processes required to bring products to market. That is especially true for mass-produced hardware, including PCs and smart phones, whose success depends on watchful vendors overseeing massive, extraordinarily complex manufacturing processes.
Effective planning, scheduling and performance are vital to hitting or missing production goals and satisfying paying customers and shareholders. That is what makes Lenovo’s new Smart Production Planning System particularly intriguing. Lenovo’s solution was recently named a finalist by the Institute for Operations Research and the Management Sciences (INFORMS) for its Franz Edelman award for operational achievement. Let’s consider it further.
To begin, what makes planning the manufacture of common products, like laptop PCs so difficult? Consider first what might be called “customer variables.” As demand and markets for tech products have evolved, vendors differentiate themselves by offering clients a wide variety of features and options to choose from.
In the case of laptops, those typically include separate brands and product families for specific use cases, like 2-in-1s, consumer/student laptops, business solutions, gaming laptops and mobile workstations. Then there are optional choices, such as upgrades for CPU/GPU, memory, storage, displays, networking, operating systems and productivity apps. Plus, security and other services, warranties, accessories and peripherals.
This is all great for customers, including organizations that can effectively customize orders so that new laptops address their specific business requirements and use cases, as well as the preferences of individual users. But ensuring that those products are assembled correctly and shipped on time poses significant planning challenges.
Fulfilling customer orders typically involves dividing manufacturing processes into tasks that are assigned to specific production lines. Planning and scheduling individual tasks involves other issues, including staff availability, equipment and process status and the availability of tens of thousands of components and raw materials. Effectively managing those scenarios while avoiding known and unknowable pitfalls is what keeps factory planners up at night.
Lenovo’s AI-enabled solution
What has Lenovo done to address these challenges? Developed by Lenovo Research, the Smart Production Planning System combines AI technologies and mathematical algorithms, including emerging sequential planning algorithms based on deep reinforcement learning, into an easy-to-use optimization decision-making engine for manufacturing. The system also supports autonomous learning—the longer it runs, the smarter it gets.
The Smart Production Planning System has been deployed at Lenovo’s LCFC (HeFei) Electronics Technology facility, the company’s largest global research and manufacturing base. The LCFC’s thousands of employees fulfilled 690,000 customer orders last year, utilizing unique production processes and over 300,000 different materials to produce more than 500 specific PC products.
So how did the Smart Production Planning System do? According to Lenovo, manufacturing planning processes at the LCFC have been reduced from six hours to 90 seconds. Additionally, key performance indicators have also improved significantly. The LCFC facility’s order fulfillment rate has increased by 20 percent and productivity has increased by 18 percent.
The System also supports large-scale collaboration and multi-objective tasks, such as real-time adjustment and configuration according to users’ specific production objectives. LCFC workers can also set hyper-parameters on the System, such as prioritizing individual manufacturing segments’ production goals to keep them aligned with shifts in demand and the manufacturing environment.
According to Lenovo, the Smart Production Planning System at the LCFC is the first time in the industry that AI technology has been deployed to enhance large scale production scheduling operations. The results are clearly positive, and it will be fascinating to see how the System’s autonomous learning capabilities impact production over time.
The solution reflects well on Lenovo Research and should continue to positively impact the company’s production efficiency and bottom line. Just as importantly, as the System evolves, it should open new commercial opportunities for the company’s service and solution-led efforts in vertical industries. In fact, it seems highly likely that other large-scale manufacturers will want to capture the same kinds of efficiency and performance benefits that the Smart Production Planning System is already providing to Lenovo.
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