Ericsson Upgrades Nanjing, China Smart Factory for 5G Radio Production

Ericsson took a major leap forward this September as it concluded its 18-month, SEK500 million (US$51.6 million) transformation of its factory in Nanjing, China. The factory manufactures 5G and 4G radio technology products, catering mostly to communication service providers in the Chinese market.

The improvements to the factory include:

• An upgraded automatic packing line
• The introduction of the first modular-designed automatic assembly line for 5G base station radios
• Modernized 5G testing equipment
• Utilization of analytics, Artificial Intelligence (AI), and Machine Learning (ML) tools
• State-of-the-art cellular Internet of Things (IoT) technologies implemented at 45 work stations that allow for increased responsiveness to critical issues and faults 

This development is part of Ericsson’s overall global supply chain management strategy, as the emphasis it places on localization allows Ericsson to service its customers more efficiently in their respective European, Asian, and American markets. The company also collaborated with Nordic-based service provider Telia earlier this quarter (3Q 2019), installing a private cellular network in its Estonia factory. The factory is streamlined through the utilization of Autonomous Guided Vehicles (AGVs), Augmented Reality (AR) interfaces, and sensors for the monitoring of environmental indicators such as moisture, temperature, noise, light, and carbon dioxide. As for the American region, Ericsson plans to establish an automated, 5G-enabled smart factory (that only requires an estimated 100 employees) in Lewisville, Texas that is expected to be fully operational by 2020.

Despite the allure of autonomous, self-organizing factories that are highly-connected, the manufacturing industry still exhibits some caution in adopting Industry 4.0 practices. Factors such as implementing the right sensors, getting secure network connectivity, selecting the right platform, and preserving operational technology compatibility are a few of the many considerations that arise. With that said, technology vendors hope to diminish the skepticism toward radical digitization by using their own factories as examples of smart manufacturing put into practice.

Bosch is applying these smart manufacturing techniques in its factory in Worcester, England. For example, the factory’s preventive maintenance measures use 5G to efficiently monitor the health of their machinery in real time. This is done through the utilization of XDK sensors that keep track of various indicators of machine usability. These sensors are also used to extend the relevance of older machines in the factory via retrofitted connectivity, allowing for analytical applications like predictive maintenance. Bosch also uses the unifying standards of Time Sensitive Networking (TSN) and Open Platform Communications Unified Architecture (OPC UA) in the digitization of its factories. OPC UA is an open standard information model that specifies information exchange for industrial communication, while TSN is a collection of IEEE802.11 standards that promotes Quality of Service (QoS) for ethernet communication and allows different applications and protocols to share the same network infrastructure. The combination of OPC UA and TSN allows for seamless interoperability between devices, enterprise, and cloud computing. These methods, among many others, have increased Bosch’s Blaichach, Germany factory’s volume output of its Antilock Braking System (ABS) and Electronic Stability Program (ESP) products by 200% in the last six years, an accomplishment that was achieved without expanding facilities or making acquisitions. The evident efficiencies these practices bring to their factories’ processes, coupled with the steady, robust demand in the market, has led Bosch to set an incremental revenue target of EUR€1 billion per year by 2022.

Siemens has also established its own factories, in Amberg, Germany and Chengdu, China, as successful use cases of their own Industrial Internet of Things offerings. Siemens Electronic Works Chengdu (SEWC), situated in the Chengdu Hi-Tech Industrial Development Zone (CDHT), uses highly digitalized End-to-End (E2E) processes in the production of its SIMATIC IPC 3000 Smart, a PC-based controller tailor-made for Chinese manufacturers. SEWC was modelled after Siemens’ Amberg factory. Electronic Works Amberg (EWA) has been in operation since 1989, and recently won Germany’s Industrie 4.0 award. With the help of its proprietary SIMATIC products, the EWA builds 120 product variations per day based on processes that are 75% automated. The company also handles more than 350 changeovers per day and 5,000 work plan changes per year (with more than 20% due to component discontinuation). Despite the scale and complexity of its operations, the factory has managed to improve on its quality and efficiency metrics through the interlinking of design and production of its Product Lifecycle Management (PLM) software, Teamcenter. This software enables modifications to enter production processes reflexively. Its digital prototyping feature allows the simulation of manufacturing processes to best determine which production process is to be adapted for the products to be made. All these measures have reduced Time to Market (TTM) cycles by 50%, with a production cycle of one product per second.

The eventual value creation and efficiency gains that come with Industry 4.0 are irrefutable. This movement, however, needs industry vanguards that provide fully functional Proof of Concepts (POCs) that can help soften companies’ cautionary dispositions. Ericsson’s recent smart factory rollouts serve as great examples for product managers of discrete manufacturing firms deliberating on adopting Industrial Internet of Things (IIoT)-enabled processes on their own factory floors:

• The first step that goes into making a holistically integrated IIoT factory floor is establishing connectivity between machines and underlying software. Manufacturers need to introduce new connections between their Programmable Logic Controller (PLC)/Human Machine Interface (HMI) hardware, Supervisory Control and Data Acquisition (SCADA) systems, Manufacturing Execution Systems (MES), and Enterprise Resource Planning (ERP) systems (and to the cloud for the accumulation and synthesis of big data). Having a tight loop of communication between hardware and software is crucial for data collection. Collected data points including temperature, proximity, vibrations, etc. from the physical endpoints, such as Ericsson’s Narrowband-IoT (NB-IoT) sensors in its smart factories, are the cornerstones of highly accurate, context-driven decisions that boost operational efficiency.
• This established connectivity between hardware and software would open a reservoir of information. Implementing companies should capitalize on the abundance of this influx of unstructured information by employing adequate data analytics tools that empower decision making through prescriptive, descriptive, or predictive analytics. Data analytics tools find correlations across multiple variables in real time. This would assist firms in executing mission-critical decisions automatically and mitigate the ever-present possibility of human error. In its Nanjing factory, Ericsson has embedded 1,000 high-precision screwdrivers (each costing US$1,500) with a US$20 module. The modules send datapoints of the utilization and maintenance requirements of each screwdriver to a central location. This predictive maintenance has allowed Ericsson to streamline the management of its resources, reducing maintenance staff by two-thirds and allocating them to other projects.
• Ericsson’s expansion also gives companies a deeper understanding of how IIoT solutions can help them augment their global supply chain management and move away from centralized manufacturing toward the more agile distributed factory model. The confluence of smart manufacturing and Ericsson’s regionalization initiatives in setting up factories in the United States, Europe, and Asia positions it to be reactive to each region’s market dynamics. The access to data enabled by IIoT techniques also enables convenient oversight of part traceability, which produces accurate reports, proper assessment of its environmental impact, and the efficient utility of assets and working capital deployment. Having full control of all aspects of PLM and pairing it with intimate knowledge of local demand would lead to more efficient production schedules and delivery times.