Facility Design
Assembly Line
The complexities of a cleanroom equipment installation
The equipment itself, as well as the installation procedures, must not compromise the cleanroom’s controlled environment. To ensure this, it must be included in the production and packaging process.
Certain cleanroom equipment, including chemical wet stations, require a clean-down procedure that matches the final location, such as fabs, which have strict contamination control protocols.
The construction of any process station begins with contamination-laden processes, especially in solvent-biased stations built from stainless steel (Figure 1). This is unavoidable.
Therefore, Felcon cleanroom equipment undergoes a continuous cleaning procedure from each department to the final packing and wrapping procedure before dispatch.
Remote site evaluations: upgrading automotive manufacturing facilities for EVs
For manufacturers, a significant factor to resolve is the weight of EVs. Electric vehicles are on average 20%-30% heavier than their combustion engine equivalents due to the lithium-ion batteries and the more robust components required to handle this additional weight.
The extra weight of EVs can place significant pressure on conveyors when handling multiple vehicles in a production line. Over the long-term, this will inevitably slow down production, resulting in inefficiencies, rising costs, and delays in time-to-market. Consequently, one of the biggest challenges facing manufacturing facilities is reinforcing conveyors with steel to enable them to operate as efficiently under heavier loads.
Using NavVis Digital Factory Solution, for example, building managers can gain a complete 3D survey of their facilities and the precise spatial data inside at a global scale, eliminating the need for physical assessments before engineering works can begin.
Multi-objective optimisation of a logistics area in the context of factory layout planning
The manufacturing factory layout planning process is commonly supported by the use of digital tools, enabling creation and testing of potential layouts before being realised in the real world. The process relies on engineers’ experience and inputs from several cross-disciplinary functions, meaning that it is subjective, iterative and prone to errors and delays. To address this issue, new tools and methods are needed to make the planning process more objective, efficient and able to consider multiple objectives simultaneously. This work suggests and demonstrates a simulation-based multi-objective optimisation approach that assists the generation and assessment of factory layout proposals, where objectives and constraints related to safety regulations, workers’ well-being and walking distance are considered simultaneously. The paper illustrates how layout planning for a logistics area can become a cross-disciplinary and transparent activity, while being automated to a higher degree, providing objective results to facilitate informed decision-making.
Making air conditioner manufacturing cool again
In just six months, Liebherr-Transportation Systems completely reconstructed two manufacturing lines, significantly upgrading them in the process. “The facility was divided into these three manufacturing lines because the three areas require very different manufacturing steps, and need to handle components of differing sizes,” Ahmad said.
The manufacturing lines – apart from the E-Box manufacturing – were first set up and tested in Korneuburg. What was especially pleasing to the two responsible persons in Korneuburg was the fact that many previously absent technologies were being used. A Kanban material delivery system and semi-automatic test steps were developed, the manufacturing became paperless, and the issue of safety gained an entirely new importance as it was able to be completely revisited.
The new production lines use, among other things, the intelligent deTec safety light curtains, TR110 Lock safety switches with locking function, various safety command devices (like emergency stop, reset, and enabling switches), signal lamps, various safety switches, and the versatile, programmable Flexi Soft safety controller.
Revolutionizing Design: The Power Of Generative AI
One of the key benefits of Generative AI in architectural design is its ability to optimize designs for specific criteria or constraints. For example, an architect could use Gen-AI to explore different options for a building’s energy efficiency or structural stability. By inputting specific parameters such as materials, site conditions, and budget constraints into the algorithm, Gen-AI can generate multiple design options that meet those requirements (e.g. establishing the column numbers in a parking garage structure).
With text-to-image generation tools becoming more accessible and user-friendly, artists without extensive technical skills can create higher-quality digital art with ease. This breakthrough has the potential to streamline the design process for clients and architects, allowing both to bring concepts to life faster than ever before. The LookX.AI text-to-image application represents a significant step forward for visual content creation by enabling users to create high-quality imagery quickly and efficiently while also pushing boundaries beyond what was previously possible using traditional methods.
ipolog Factory Viewer: Revolutionieren Sie Ihre 3D-Planung
Explainable generative design in manufacturing for reinforcement learning based factory layout planning
Generative design can be an effective approach to generate optimized factory layouts. One evolving topic in this field is the use of reinforcement learning (RL)-based approaches. Existing research has focused on the utilization of the approach without providing additional insights into the learned metrics and the derived policy. This information, however, is valuable from a layout planning perspective since the planner needs to ensure the trustworthiness and comprehensibility of the results. Furthermore, a deeper understanding of the learned policy and its influencing factors can help improve the manual planning process that follows as well as the acceptance of the results. These gaps in the existing approaches can be addressed by methods categorized as explainable artificial intelligence methods which have to be aligned with the properties of the problem and its audience. Consequently, this paper presents a method that will increase the trust in layouts generated by the RL approach. The method uses policy summarization and perturbation together with the state value evaluation. The method also uses explainable generative design for analyzing interrelationships between state values and actions at a feature level. The result is that the method identifies whether the RL approach learns the problem characteristics or if the solution is a result of random behavior. Furthermore, the method can be used to ensure that the reward function is aligned with the overall optimization goal and supports the planner in further detailed planning tasks by providing insights about the problem-defining interdependencies. The applicability of the proposed method is validated based on an industrial application scenario considering a layout planning case of 43 functional units. The results show that the method allows evaluation of the trustworthiness of the generated results by preventing randomly generated solutions from being considered in a detailed manual planning step. The paper concludes with a discussion of the results and a presentation of future research directions which also includes the transfer potentials of the proposed method to other application fields in RL-based generative design.
Optimizing factory planning in the automotive industry
Factory planning in the automotive industry presents a multifaceted endeavor with numerous complexities. Some of the most prominent factors that demand careful attention are factory layout optimization, space constraints, and adapting to the paradigm shift toward Electric Vehicles (EVs).
Efficient factory layout design is crucial for enhancing production efficiency, reducing material movement, and ensuring a safe, ergonomic work environment. Achieving this optimization can be intricate, demanding careful consideration of equipment placement and manufacturing process.
Toyota takes on Tesla’s gigacasting in battle for carmaking’s future
Some car executives and analysts expect Tesla’s process — which Musk calls “gigacasting” — to set a new benchmark for building vehicles, replacing the vaunted Toyota Production System based on just-in-time manufacturing efficiency. The way Tesla is making cars “is quickly moving to become an industry standard”, said one senior executive at a European automaker.
For the moment, Toyota says it wants more than half of its 2030 sales target to be made up of EVs using its new modular architecture, which allows it to produce multiple different models, that share key components, on the same platforms. Yuzawa said: “Gigacasting is going to reshape the whole underbody supply chain network.”
Why Sandy is Captivated By Castings: IDRA Conference Recap
It Takes Two: Why Digital Twins Need Both Humans and Machines
When Western Digital expanded its hard drive manufacturing site in Thailand, the first time the assembly lines were turned on wasn’t on the factory floor; it was on a laptop 8,000 miles away. Before any physical machinery found its place within the newly constructed walls, teams of engineers meticulously crafted its virtual counterpart. This digital twin could mimic the operations down to every tool, robot arm, and even the pace of human operators, flawlessly simulating the assembly of the company’s most advanced enterprise hard drives. Engineers could quickly test different layouts and operation scenarios without touching the production line.
For most projects, Sanguanpong could go into the factory and measure parameters like cycle times, yield, output, or level of automation. Here, she needed to extrapolate data from experts about machines and processes that had yet to materialize. “Because there is no physical operation in the building, we the advanced analytics team needed to validate our findings with the subject matter experts, making sure our simulation model fit the expected action,” she said. Data needed to constantly flow in and out of the model, relying not only on algorithms but on the capacities of human communication and imagination.
Innovating Metallurgical Equipment Design to Meet Flotation Plant Layout Challenges
One of the key design principles that holds true is that minimizing the equipment’s hydraulic head requirements can potentially minimize the number of pumps needed in a plant. This not only reduces energy demand, but also lowers operational and maintenance costs. Additionally, by minimizing the head requirement, one can free up space for additional process functions needed in the plant.
An example of this principle in action is the design of large flow rate sampling equipment. Traditional sampling systems for flow rates of 35,000 cubic meters or more often require splitting the final tails into two samples, which results in complex reconciliation and recombination processes. However, samplers that can operate at flow rates of up to 40,000 cubic meters an hour and incorporate all sampling stages at one floor level not only simplifies the process, but also saves height in the tails of the plant, reducing the overall cost of construction.
Why vibration control is key to semiconductor manufacturing
Although these manufacturing sites can be vast, most of the equipment is not directly used in the manufacture of silicon chips. Manufacturing at the nanoscale requires highly controlled conditions, so the fabs require an extensive range of heating, cooling and filtration systems. This plant equipment makes up approximately 90% of the equipment located at a typical fab.
This equipment ensures the correct temperature, humidity level and particulate level for the optimal production of chips. However, while solving one problem, it also introduces another. Mechanical systems and HVAC systems all generate vibration which, if left unmitigated, could disrupt sensitive precision manufacturing processes and interfere with chip production. ‘‘Vibration control is key to making these things work,’’ Adam explained.
One of the unique features of this project was the vast scale. In total, there were approximately 130 kilometres of piping and 3.2 kilometres of ductwork. The project therefore required a staggering 3,800 mounts. ‘‘I’ve worked on all sorts of projects at this stage of my career, but nothing can touch this one in terms of scale. Nothing is even close,’’ Adam reflected.
Assystem Creates a Digital Twin for Nuclear Plants with Altair
Advanced expertise required to execute complex cold storage warehouses
Constructing a state-of-the-art cold storage facility is only possible with the right building site. Location is key and must be close to where food is grown and/or harvested or near other manufacturing locations. The site needs access to interstates and potentially to railways, ports and waterways. A traffic assessment is necessary to determine whether the site can accommodate construction traffic and business-related traffic once the facility is in operation.
Because developers cannot build out in most urban and suburban areas, increasing the building’s footprint, they’re building up. These tall buildings often use automated storage and retrieval systems (AS/RS) designed to operate in vertical spaces. While evaluating AS/RS, it is essential to consider the factors that help drive the level of automation within a building.
In addition to labor costs, inventory turnover and SKU variety, other factors to consider may include, but may not be limited to, performance (design throughput versus actual) and proforma duration (reasonable expectation of improved performance over time). A pragmatic evaluation of these factors may prove to be a prudent approach in selecting the degree of automation within a facility.
Inside GE Appliance's State-of-the-Art Water Heater Assembly Plant
A variety of manufacturers produce electric and hot water heaters for residential applications, including GE Appliances, a Haier company. To increase production capacity, it recently invested $70 million in a state-of-the-art manufacturing plant in Camden, SC. The 265,000-square-foot facility also serves as the company’s Center of Excellence for water heater manufacturing. The investment included advanced systems for metal fabrication and welding, plus robots for material handling and processing.
GE Appliances’ engineers carefully considered quality, safety and ease of manufacturing when designing and laying out the plant. “Automation was selected to provide predictable, consistent quality of products in an environment that is safe and ergonomically friendly to our operations team,” explains Zimmer.
“We focused on creating a production process centered around operators,” says Scheffel. “We looked at different approaches to ensure the best way to present parts from an ease of access point of view. We paid special attention to ergonomics to ensure there were zero ‘ergo red’ jobs on the plant floor.
“In addition, the other big consideration was the efficient flow of material through the plant,” notes Scheffel. “For instance, we made the final assembly line a forklift-free zone. All materials are delivered to workstations with automated guided vehicles and tuggers.”
Fine-Tuning the Factory: Simulation App Helps Optimize Additive Manufacturing Facility
“The model helps predict how heat and humidity inside a powder bed fusion factory may affect product quality and worker safety,” says Adam Holloway, a technology manager within the MTC’s modeling team. “When combined with data feeds from our facility, the app helps us integrate predictive modeling into day-to-day decision-making.” The MTC project demonstrates the benefits of placing simulation directly into the hands of today’s industrial workforce and shows how simulation could help shape the future of manufacturing.
The team made their model more accessible by building a simulation app of it with the Application Builder in COMSOL Multiphysics. “We’re trying to present the findings of some very complex calculations in a simple-to-understand way,” Holloway explains. “By creating an app from our model, we can empower staff to run predictive simulations on laptops during their daily shifts.”
Visual Components Connector for NVIDIA Omniverse: The future of Manufacturing Planning
A Framework for Ensuring Safe Plant Design and Operation in the Process Industries
The safety of industrial plants is a prerequisite for reassuring local communities and achieving a sustainable society. The process industries operate large, complex man-machine systems and even a single accident in a plant could cause immense damage to facilities, local communities, and the environment, and, in an extreme case, could destabilize the whole of society. To prevent such serious accidents, laws and regulations concerning process safety were discussed globally and the concept of risk reduction with multiple protection layers and a management system through the design and operation of safety instrumented systems was established as a framework for the safety of the process industries. This paper reviews this framework with reference to the trend of related standardization activities and introduces how AI is used to support safety in the process industries.
Fields of action towards automated facility layout design and optimization in factory planning – A systematic literature review
The success of a factory planning project is significantly influenced by the layout design. It contributes to make the production process more economical and reliable. Studies show that an effective layout can reduce the operating costs of a factory by up to 30%.
Layout design is a very complex planning problem characterized by the conflict between competing goals and restrictions. Both quantitative goals, such as material flow, and qualitative goals, like communication and adaptability of a layout, must be taken into account. In addition, regulatory requirements and norms, which are the restrictions the design is based on, must also be met.
Despite the high complexity, the arrangement of the operational functional units is usually done manually, either on paper or with a digital layout design software. The layout variants are then evaluated by experts to identify the optimal layout.
A Platform Based on the Semantic Data Model That Makes Full Use of Design Data throughout the Plant Lifecycle
Design data are created in multiple systems because their purpose and specialty are different. Yokogawa has been developing a plant data transformation platform that checks the consistency among data distributed across various systems and enables the interoperability of the data by applying ontology technology to database operation and management. This platform will make it possible to quickly and reliably resolve data gaps and inconsistencies between the plant design and instrumentation systems, ensure their reliability, and provide high-quality engineering services. This paper describes through the value architecture analysis how this platform technology will also help solve social issues related to the SDGs and explains its core technologies and application examples.
Designing Basic & Detailed Processes for Mega Methanol Plants
A thorough understanding of the processes required for a methanol plant is necessary for the selection of pumps, valves and hoses that will give life to the production facility. Specifying the types and grades of equipment required at the plant was a collaborative effort between Gabriel and the product specific experts.
The number of valves used in a mega methanol plant exceeds expectations. When asked, Gabriel expressed that “there are literally thousands of valves involved in a project like this one. There are probably 1,200 automated control valves in this plant, and that estimate does not take into account any of the manual valves used throughout the facility.” The valves he found to be the most engaging were critical process valves; high pressure steam valves, gas valves, methanol valves and oxygen valves. Each of these valve types requires extra attention and are typically custom made to suit the projects needs.