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As the world’s first A-class auto show in 2023, the Shanghai International Automobile Industry Exhibition kicked off yesterday, and many new technologies, new products and new concepts have become the focus of the market.

By 2022, China has ranked first in the world in automobile production and sales for 14 consecutive years. At present, around the new transformation trend of “electrification, networking, intelligence and sharing”, many car companies are actively laying out new tracks and accelerating towards a new era of green intelligence. Behind the transformation and upgrading of the automobile industry, Siemens continues to contribute scientific and technological strength.

Just yesterday, Dr. Xiao Song, Chairman, President and CEO of Siemens China, attended the Shanghai International Auto Show and had in-depth communication and exchanges with many entrepreneurs to discuss cooperation and seek common development.

Xiao Song, Chairman, President and CEO of Siemens China, said that the automobile industry is one of the pillar industries of China’s economy, plays an important role in boosting consumption and stabilizing the overall economy, and is also a key tool for China to develop a digital economy and achieve the “dual carbon” goal. With the “dual-wheel drive” of digitalization and low-carbonization, combined with deep industry knowledge and experience, we will continue to work closely with automobile companies to expand new opportunities, create new advantages, and accelerate the high-quality development of the industry.

At the auto show, Dr. Xiao Song witnessed the signing of a strategic cooperation agreement between Siemens and Xiaopeng Motors. The two parties will rely on Siemens’ innovative technology and industry insights in the fields of industrial digitalization, smart parks, smart energy, and green and low-carbon development to help Xiaopeng Motors actively explore new models of intelligent manufacturing for the future.

Chery was very international at this Shanghai Auto Show, fully displaying 14 new energy vehicles from its four major brands. Siemens and Chery have been cooperating for nearly 20 years, and the two parties are actively deepening their long-term cooperation in digital R&D, manufacturing, integrated energy management, green and low-carbon development, and other fields.

The Lotus booth was particularly eye-catching at this auto show, allowing the audience to experience the charm of cutting-edge technology firsthand. From automation hardware to data management and simulation software, Siemens’ “digital twin” technology is helping Lotus factories break information silos and improve efficiency and flexibility from R&D to manufacturing.

At this auto show, auto parts manufacturer Schaeffler focused on three major areas: electrification, chassis applications and commercial vehicles, and displayed a series of innovative products and solutions. Schaeffler has extensive cooperation with Siemens. Among them, Schaeffler’s benchmark factory in Taicang, Jiangsu, applied Siemens’ low-code development platform to establish a complete set of paperless solutions, significantly improving resource efficiency.
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Faced with the global trend of accelerating transformation of new energy vehicles, automakers urgently need to consider a new way of working. Sinotruk seized the opportunity and actively explored industrial digitalization and automation with the support of ABB’s world-leading intelligent manufacturing technology, and successfully won the “double first” in sales and market share of domestic heavy-duty truck companies in 2022.

Sinotruk’s “Intelligent Networked (New Energy) Heavy-Duty Truck Project”, namely Sinotruk Laiwu Smart Factory, is a digital “lighthouse factory” built by Sinotruk after its restructuring and reform, and it is also the most digitalized factory in Sinotruk Group today. ABB provided a total of 111 robots, a series of digital products and flexible solutions for its welding workshop, creating Sinotruk’s first automated production line for the “Yellow River” series of a new generation of high-end logistics traction heavy-duty trucks.

The complete welding solution provided by ABB for Sinotruk Laiwu Smart Factory uses IRB 6700 and IRB 7600 robots, covering the entire process of the welding factory, involving material preparation, floor line, side line, main line, door line and adjustment line areas, and high-precision welding ensures production quality. At the same time, ABB FlexTrack seven-axis guide rails are widely used, which greatly improves the body transmission speed with its excellent motion performance.

In the early planning stage of the project, after continuous polishing and testing, ABB and Sinotruk Group finally unanimously decided to innovatively use the ABB FlexProd production line layout solution in some workstations: split the traditional long-line production architecture of the car factory and deploy dedicated modular units. Using this cutting-edge car factory layout concept, Sinotruk Laiwu Smart Factory can replace or adjust a single workstation at any time to avoid production interruption problems. At the same time, with flexible AGV logistics, it replaces manual loading and unloading links, enabling production processes to be more flexible and productive.

In addition, ABB also provides the ModulFlex automatic fixture switching library for the production line, which supports multi-model switching without affecting the production rhythm; with ABB FlexPLP flexible programmable linear positioner, it greatly improves the accuracy of body positioning and welding quality. Today, the welding production line provided by ABB for Sinotruk Laiwu Smart Factory mainly produces heavy-duty truck products such as the Yellow River series and the Howo TX series, with an annual output of up to 50,000 vehicles.

The first cooperation between ABB Robotics and Sinotruk can be traced back to 2010. At that time, ABB built the group’s first body-in-white welding production line for Sinotruk. With more than ten years of cooperation, ABB will continue to help Sinotruk achieve continuous transformation and upgrading from traditional vehicle products to new energy, intelligent networked green products through leading automation technology and solutions in the future, further consolidate Sinotruk Group’s position as a leader in cutting-edge technology for China’s heavy-duty vehicles, and work together to create a bright business card for Chinese commercial vehicles to go global.

China National Heavy Duty Truck Group Co., Ltd. (hereinafter referred to as “Sinotruk”) was founded in 1930 and owns a full range of well-known commercial vehicle brands such as Yellow River, Shandeka, and Howo. Products are exported to more than 110 countries and regions, and have maintained the top export position in the national heavy-duty truck industry for 18 consecutive years. Since undergoing restructuring and reform in 2018, Sinotruk has accelerated its pace of independent innovation and has strongly jumped to the “double first” in sales volume and market share in China’s heavy-duty truck industry in 2022.
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Vimal Kapur, CEO of Honeywell, one of the world’s largest industrial conglomerates, sees AI differently than most. AI is not about threatened office workers. “Every five years there’s a trend that makes your skills obsolete,” Kapur said at the recent CNBC Evolution: The AI ​​Opportunity Summit in New York. “The loss of white-collar workers is an ongoing evolution.” AI, he said, is not about the cool features it can offer consumers, who “get excited about writing resumes or restaurant recommendations.” The biggest problem AI can solve for Honeywell is first and foremost the labor shortage it and its client companies face. From pilots to technicians, falling birth rates in industrialized countries have led to fewer and fewer jobs that were popular 25 years ago. “Everyone in industry has this problem,” he said. Honeywell’s AI opportunity is about creating a new pool of labor that can learn and work alongside AI and accumulate and deploy institutional knowledge faster. Traditionally, he said, humans needed 15 years of experience to handle complex roles, but someone with five years of experience working with two AI co-pilots can reach the same level.Labor isn’t the only issue with AI deployment. Kapur noted that Honeywell plans to roll out connectivity within jet engines in the coming months that will allow the company to proactively monitor engine performance to spot maintenance issues before they return to the shop. The same is true for smoke detectors, another staple in Honeywell’s product line, which will be identified as needing repair or replacement earlier than before.

But labor issues remain a top concern for the Honeywell CEO, who added that it makes him see AI as a revenue opportunity rather than a way to increase productivity. “Skills shortage is at the heart of our problem,” Kapur said. “It’s the constraint to increasing revenue. The biggest constraint to revenue is the lack of skilled labor.”

Most companies are just beginning to find a return on their AI investments, with levels of return far beyond OpenAI’s underlying large language models and Nvidia’s chipmaking.

Raw data, collected directly from the source without being filtered through intermediaries, will be the key to AI success for many companies, said Jake Loosararian, CEO of Gecko Robotics. Gecko Robotics, a company that works in energy, manufacturing and defense to optimize maintenance, has AI-powered inspection robots analyzing equipment as large as aircraft carriers to identify structural defects.

“The future belongs to companies with ‘best-in-class’ datasets,” he told Jon Fortt, host of CNBC’s “Closing Bell Overtime,” at the Evolve: AI Opportunity event.

Several executives stressed the importance of moving beyond the current focus on large language models, including one at the forefront of the LLM: Clément Delangue, co-founder and CEO of Hugging Face, one of the world’s most highly valued AI startups, backed by Amazon, Nvidia and Google. He expressed similar sentiments to Loosararian at the CNBC event. Delangue

“Data and datasets are the next frontier in AI,” he said, noting that more than 200,000 public datasets have been shared on Hugging Face, a platform that takes an open-source approach to developing AI models, and that datasets added to the platform are growing faster than new large language models.

“The world will evolve to a world where every company, every industry and even every use case has its own specific custom model,” Delangue said. “Eventually, every company will build their own model, just like they have their own code base and build their own software product… Ultimately, this will help them differentiate themselves.”

If companies gain the most from AI customized to their use cases, a view is gaining momentum in AI regulatory discussions to shift the focus from large language models to industry-specific monitoring. As these use cases proliferate, executives need to make sure they are communicated to the board.

“Board members really need to understand what use cases the company might be using so they can get a report from the people who best understand the risks the company might face,” Katherine Forrest, a former federal judge, partner at Paul, Weiss, Rifkind, Wharton & Garrison and an expert in AI law, said at the CNBC AI Summit.

Now, she said, is the time to ask: “What are the risks? Do we have the right people to manage those risks? Have we had any incidents? They should know if those risks actually occurred.”

While there is debate about how quickly AI opportunities will be realized, Honeywell’s Kapur is optimistic about a rapid steepening of the adoption curve. “Awareness is high and adoption is low, but there will be an inflection point,” he said. “I do believe 2025-2026 will be a big year for AI adoption in the industrial sector.”
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The VMIVME-7645 incorporates the latest Intel chipset technology, the 855GME. This chipset departs from previous generation devices by utilizing a new Advanced Hub Architecture (AHA). The AHA allows for increased system performance by separating many high-bandwidth I/O accesses (like IDE or USB devices) from PCI accesses, relieving bottlenecks on the PCI bus. Furthermore, the 855GME chipset brings new levels of integration to motherboard chipsets and provides additional features over other chipsets.

The Hance Rapids I/O Controller Hub (ICH) incorporates much of the hardware for the VMIVME-7645’s input/output ports, or drives the interfaces to which the controllers for the remainder of the I/O are connected. It includes support for two external PCI buses ( 32-bit 33MHz and 64-bit 66MHz), four USB ports, DMA controller, two 16550 serial ports, real-time clock, interrupt controller and Watchdog Timer.

Organization of the Manual

This manual is composed of the following chapters and appendices:

Chapter 1 – Installation and Setup describes unpacking, inspection, hardware jumper settings, connector definitions, installation, system setup and operation of the VMIVME-7645.

Chapter 2 – Standard Features describes the unit design in terms of the standard PC memory and I/O maps, along with the standard interrupt architecture.

Chapter 3 – Embedded PC/RTOS Features describes the unit features that are beyond standard functions.

Chapter 4 – Maintenance provides information relative to the care and maintenance of the unit.

Appendix A – Connector Pinouts illustrates and defines the connectors included in the unit’s I/O ports.

Appendix B – System Driver Software provides details for installing drivers under Windows XP.

Appendix C – AMI BIOS describes the menus and options associated with the AMI (system) BIOS.

Appendix D – Argon BIOS describes the menus and options associated with the LAN Boot BIOS.

Appendix E – Sample C Software provides example code to use with the VMIVME-7645.

Safety Summary

The following general safety precautions must be observed during all phases of the operation, service and repair of this product. Failure to comply with these precautions or with specific warnings elsewhere in this manual violates safety standards of design, manufacture and intended use of this product.

VMIC assumes no liability for the customer’s failure to comply with these requirements.

Ground the System

To minimize shock hazard, the chassis and system cabinet must be connected to an electrical ground. A three-conductor AC power cable should be used. The power cable must either be plugged into an approved three-contact electrical outlet or used with a three-contact to two-contact adapter with the grounding wire (green) firmly connected to an electrical ground (safety ground) at the power outlet.

Do Not Operate in an Explosive Atmosphere

Do not operate the system in the presence of flammable gases or fumes. Operation of any electrical system in such an environment constitutes a definite safety hazard.

Keep Away from Live Circuits

Operating personnel must not remove product covers. Component replacement and internal adjustments must be made by qualified maintenance personnel. Do not replace components with power cable connected. Under certain conditions, dangerous voltages may exist even with the power cable removed. To avoid injuries, always disconnect power and discharge circuits before touching them.

Notation and Terminology

This product bridges the traditionally divergent worlds of Intel-based PC’s and Motorola-based VMEbus controllers; therefore, some confusion over “conventional” notation and terminology may exist. Every effort has been made to make this manual consistent by adhering to conventions typical for the Motorola/VMEbus world; nevertheless, users in both camps should review the following notes:

Hexadecimal numbers are listed Motorola-style, prefixed with a dollar sign: $F79, for example. By contrast, this same number would be signified 0F79H according to the Intel convention, or 0xF79 by many programmers. Less common are forms such as F79h or the mathematician’s F7916

An 8-bit quantity is termed a “byte,” a 16-bit quantity is termed a “word,” and a 32-bit quantity is termed a “longword.” The Intel convention is similar, although their 32-bit quantity is more often called a “doubleword.”

Motorola programmers should note that Intel processors have an I/O bus that is completely independent from the memory bus. Every effort has been made in the manual to clarify this by referring to registers and logical entities in I/O space by prefixing I/O addresses as such. Thus, a register at “I/O $140” is not the same as a register at “$140,” since the latter is on the memory bus while the former is on the I/O bus.

• Intel programmers should note that addresses are listed in this manual using a linear, “flat-memory” model rather than the old segment:offset model associated with Intel Real Mode programming. Thus, a ROM chip at a segment:offset address of C000:0 will be listed in this manual as being at address $C0000. For reference, here are some quick conversion formulas:

Segment:Offset to Linear Address

Linear Address = (Segment × 16) + Offset

Linear Address to Segment:Offset

Segment = ((Linear Address ÷ 65536) − remainder) × 4096

Offset = remainder × 65536

Where remainder = the fractional part of (Linear Address ÷ 65536)

Note that there are many possible segment:offset addresses for a single location. The formula above will provide a unique segment:offset address by forcing the segment to an even 64 Kbyte boundary, for example, $C000, $E000, etc. When using this formula, make sure to round the offset calculation properly
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