Design Engineering Automation for Highly Configurable Products

Manufacturers of highly configurable products want to maximize engineering resources. By capturing knowledge and decision-making, the newest best-in-class engineering automation software speeds development of subsequent design iterations. Automating rules for engineer-to-order (ETO) manufacturers configures custom versions; these technologies allow custom products to reach markets faster and with less friction. More compelling proposals, higher quality products, and reduced engineering costs provide a rapid ROI (return on investment).

A typical design engineering cycle and common questions
Design Engineering Automation for Highly Configurable Products
 
The questions accompanying product design are many and there are no easy answers. Automation offers shortcuts that deal with these various challenges. Answering these common questions via automation technology frees engineers to do more fulfilling, interesting, and rewarding work.

Many engineer-to-order manufacturers are able to manage configured products more effectively when automation is implemented especially during product engineering, development, and release cycles.  Manually, design errors increase exponentially.

Powerful automation tools
There are powerful automation tools for defining product structures, managing configuration rules (between products and across solutions), as well as understanding the interactions of options and components in complex products. These tools empower users to make faster, more effective design decisions. Through configuration analysis, BOM (Bill of Material) validation, and collaborative modeling, engineering automation achieves faster time to market with higher quality products at lower costs.

Excel-like simplicity helps create 3D product models and assemblies
Highly configurable products cannot be effectively managed using spreadsheets alone. Solutions like Knowledge Bridge (kBridge) operate a lot like Excel. Unlike Excel, the technology builds hierarchical product models, due to the native ability to identify and drive top-level design parameters. Users most appreciate fast, simple-to-use 3D graphics.

Engineers mired in non-automated work-around solutions (and frustrated with the segregation of spreadsheet information from design engineering) crave simple and robust engineering tools. Typically, engineers’ top complaint in the manual ETO space is the constant repetition of boring, tedious operations.

Automating operations
Once implemented, engineers can work on well-engineered and dynamic designs because the repetitive issues have been removed. The right tools allow engineers to create solidly engineered products and capture knowledge in a model, then re-use it any time needed in the future.
 
Growing engineering knowledge base must be incremental and easy
Design Engineering Automation for Highly Configurable Products
©2021 Engineering Intent kBridge

Best-in-class design engineering solutions must reside in the cloud. Domain experts capture engineering, sales, geometric, and configuration rules for an ETO product. UI (user interface) tools create data that non-technical personnel can use. Inputs include product engineering parameters and geometry as well as business rules and customer-specific information. Outputs include a variety of documents, including proposals, quotes, drawings, integrations with CAD/PDM, and data.

Technology must support evolutionary product design without disrupting work as users capture and grow a company’s knowledge base of engineering design capital. Design engineers must be empowered to explore options and incrementally improve product solutions through design iteration. Enterprise engineering knowledge captured in solutions can be shared and improved. No longer tribal knowledge these data can be shared to train new engineers.

“Engineer think” versus “Accountant think”
Experts are able to express product requirements, configure customer designs visually, and automate the to-order work in familiar environments (similar to a spreadsheet). Rule-making is aligned with the way engineers think versus a spreadsheet, where number-crunching is aligned with the way accountants think. Customers want custom designs and documentation. The best-in-class tools combine custom engineered content with existing materials which reduces the engineering design hours without compromising the client’s specifications.
About The Author
Scott Heide, Founder, CEO, Engineering Intent
With more than 30 years of experience in knowledge-based engineering software, Heide has long been a key source for industry understanding of and application strategies for engineering and sales automation. Heide drove the development of Knowledge Bridge, a cloud-based comprehensive EPQ (Engineer Price Quote) and visual configuration platform. It offers tools and methods to automate custom engineering, technical sales, and business processes – the “To Order” in “Engineer To Order”.
Heide holds a Bachelor of Science in Mechanical Engineering from Wichita State University and a Master of Science in Engineering from the Massachusetts Institute of Technology. Connect on LinkedIn.

SPOTLIGHT

Engineering Intent is the World's Leading Provider of Enterprise Engineering Automation Tools and Solutions. We've been helping companies tame their complex product configuration solutions for decades.

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Manufacturing Production Planning and Control: What, Why, and How?

Article | January 3, 2022

Production planning and control are critical components of any manufacturing organization. It helps organizations with the regular and timely delivery of their goods. Furthermore, it allows manufacturing businesses to increase their plant’s efficiency and reduce production costs. Numerous software and tools for production scheduling and planning are available on the market, including Visual Planning, MaxScheduler, and MRPeasy, which assist manufacturing organizations in planning, scheduling, and controlling their production. According to KBV Research, the manufacturing operations management software market is anticipated to reach $14.6 billion by 2025 globally, expanding at a market growth of 10.2 percent CAGR during the forecast period. So, what exactly is production planning and control? Production planning is an administrative process within a manufacturing business. It ensures that sufficient raw materials, personnel, and other necessary items are procured and prepared to produce finished products according to the specified schedule. Scheduling, dispatch, inspection, quality control, inventory management, supply chain management, and equipment management require production planning. Production control makes sure that the production team meets the required production targets, maximizes resource utilization, manages quality, and saves money. “Manufacturing is more than just putting parts together. It’s coming up with ideas, testing principles and perfecting the engineering, as well as final assembly.” – James Dyson In oversize factories, production planning and control are frequently managed by a production planning department, which comprises production controllers and a production control manager. More significant operations are commonly monitored and controlled from a central location, such as a control room, operations room, or operations control center. Why Should You Consider Production Planning? An efficient production process that meets the needs of both customers and the organization can only be achieved through careful planning in the early stages of production. In addition, it streamlines both customer-dependent and customer-independent processes, such as on-time delivery and production cycle time. A well-designed production plan minimizes lead time, the period between placing an order and its completion and delivery. The definition of lead time varies slightly according to the company and the type of production planning required. For example, in supply chain management, lead time refers to the time required for parts to be shipped from a supplier. Steps in Production Planning and Control Routing The first stage of production planning determines the path that raw materials will take from their source to the finished product. You will use this section to determine the equipment, resources, materials, and sequencing used. Scheduling It is necessary to determine when operations will occur during the second stage of production planning. In this case, the objectives may be to increase throughput, reduce lead time, or increase profits, among other things. Numerous strategies can be employed to create the most efficient schedule. Dispatching The third and final production control stage begins when the manufacturing process is initiated. When the scheduling plan is implemented, materials and work orders are released, and work is flowing down the production line, the production line is considered to be running smoothly. Follow-Up The fourth stage of manufacturing control ascertains whether the process has any bottlenecks or inefficiencies. You can use this stage to compare the predicted run hours and quantities with the actual values reported to see if any improvements can be made to the processes. Production Planning Example Though production planning is classified into several categories, including flow, mass production, process, job, and batch, we will look at a batch production planning example here. Manufacturing products in batches is known as "batch production planning." This method allows for close monitoring at each stage of the process, and quick correction since an error discovered in one batch can be corrected in the next batch. However, batch manufacturing can lead to bottlenecks or delays if some equipment can handle more than others, so it's critical to consider capacity at every stage. Example Consider the following example of batch production planning: Jackson's Baked Goods is in the process of developing a production plan for their new cinnamon bread. To begin with, the head baker determines the batch production time required by the recipe. He then adjusts the bakery's weekly ingredient orders to include the necessary supplies and schedules the weekly cinnamon bread bake during staff downtime. Finally, he creates a list of standards for the bakery staff to check at each production stage, allowing them to quickly identify any substandard materials or other batch errors without wasting processing time on subpar cinnamon bread. Final Words Running a smooth and problem-free manufacturing operation relies heavily on a precise production planner. Many large manufacturing companies already have a strong focus on streamlining their processes and making the most of every manufacturing operation, but small manufacturing companies still have work to do in this area. As a result, plan, schedule, and control a production that will enable you to run your business in order to meet its objectives. FAQ What is the difference between planning and scheduling in production? Production planning and scheduling are remarkably similar. But, it is critical to note that planning determines what operations need to be done and scheduling determines when and who will do the operations. What is a production plan? A product or service's production planning is the process of creating a guide for the design and manufacture of a given product or service. Production planning aims to help organizations make their manufacturing processes as productive as possible.

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Digital Twin in Manufacturing: Helping Businesses in Growing Their Revenue

Article | April 1, 2022

Digital twin technology in the manufacturing industry is playing a vital role in evaluating current and future production line conditions to increase OEE, productivity, and business profitability. It has become the most critical component of industry 4.0 because it collects precise data about your manufacturing process and uses that data to help you make wiser decisions. In other words, manufacturers can utilize digital twins to check and assess physical assets, processes, and systems in a virtual environment. In this article, we will discuss some of the major applications of digital twin technology in the manufacturing industry. Additionally, we also have a look at how this technology helps businesses increase their ROI. Digital Twin Technology Applications Product Development Product development is a long and intricate process. For example, it might take up to six years to develop and launch a new automobile model. The shift from the previous model to the new model must be seamless. A minor error during this process might have a detrimental effect on the brand's value and revenue. A digital twin software enables the integration of data between previous-generation models and the new concept's digital representations. Additionally, twinning facilitates communication between product designers, end users, and other stakeholders. When it comes to product testing, having digital twin platforms eliminates the need to wait for performance data from car trials to determine the product's performance and quality. Design Customization As consumers become more intelligent, and demand personalized items in a timely manner, the manufacturing industry will become increasingly competitive. According to an Industry Week Special Research Report on the future of manufacturing, industrial enterprises of all sizes place a premium on process improvement and customer relationship strengthening, while small businesses focus on addressing customer demand for product customization. To assist in the customization process, manufacturers use Twin Design Customization, which enables the virtual design and re-design of goods prior to generating a physical product that fully meets consumer specifications. Shop Floor Performance Improvement The shop-floor digital twin concept helps businesses to be proactive as the system is capable of identifying anomalous situations. This demands attention and process improvements prior to them escalating into a real problem or standstill. Predictive Maintenance Individual digital twin examples for equipment or manufacturing processes can detect deviations that indicate the need for preventative repairs or maintenance prior to the occurrence of a serious problem. Additionally, they can aid in the optimization of load levels, tool calibration, and cycle times. Can Digital Twin Boost Business Revenue? According to a recent study by Juniper Research, revenue from digital twins (a virtual representation of a connected physical product, process, or service throughout its lifecycle) will reach $13 billion by 2023. This is an increase from an estimated $9.8 billion in 2019, representing an average annual growth rate of 35%. The study also discovered that increased deployments of advanced sensors for data collection and technological advancements such as machine learning, artificial intelligence, and high-performance computing are enhancing the benefits of digital twins. So, how does a digital twin help your company's ROI? The digital twin improves transformation efficiency by providing platforms and technologies that simulate the impact of process changes in your supply chain – in a safe, secure, and digitally isolated environment – using real-time scenario modeling generated parallel with live supply chain operations. More than a visualization, a digital twin can help accelerate innovation, foster consensus, and save time and money by iteratively modeling changes, testing how components or systems operate, and inexpensively troubleshooting malfunctions in a virtual world. Final Words The digital twin platforms benefit manufacturing organizations across all verticals, including supply chain management, manufacturing operations, and logistics. Thus, technology is accelerating and enhancing the manufacturing industry to obtain more positive results and, in turn, increase its efficiency and, as a result, its return on investment. The digital twin will gain popularity as businesses learn to use it to their advantage. According to a 2020 analysis conducted by Research and Markets, up to 89% of all IoT platforms will incorporate digital twins by 2025. Thus, the future of digital twins is bright, and we may witness increased use of digital twins in the next few years. FAQ How digital twin help businesses? Digital twins can help businesses make better data-driven decisions. Businesses utilize digital twins to understand the state of physical assets, respond to changes, optimize operations, and add value to systems. How does digital twin save money? A digital twin can save time and money by iteratively modeling modifications, testing component or system functionality, and resolving faults in virtual reality. What are the essential components of digital twin technology? The concept of the digital twin is composed of three unique components: the physical product, the digital or virtual product, and the linkages between the two.

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Actions C-suite Executives Can Take to Get the Most Out of Cloud Computing

Article | April 26, 2022

Cloud implementation alone will not provide value for a company. Executives at the highest levels must take the initiative towards digital transformation. C-suite executives play an important role in a business's digital transformation, which is critical to its success. C-level executives must consider cloud computing plans over the long term and ensure appropriate money and resources for cloud adoption. When it comes to cloud computing's objectives and benefits, C-level executives must take the lead and be involved in the strategies to ensure that the blueprint meets the business's requirements. CEOs, for example, must collaborate with CTOs and CIOs to maximize the benefits of cloud computing and ensure a smooth transition to digital transformation. In this article, we will discuss the five essential activities that the organization's c-level executives must undertake to get the most out of cloud computing. Five Cloud Adoption Actions C-suite Executives Must Take Maintaining a Consistent Financial Flow Cloud computing's objectives and benefits can be realized only with enough funding. As a CEO, it is critical to establish a financial funnel that supports each stage of the organization's cloud migration journey. It may take time for your firm to benefit from cloud computing fully. As a result, it is critical to ensure the financial backing is steady and consistent. Develop a Cloud-based Business Strategy A business transition is only as efficient as the planning that supports it. Therefore, to maximize the value of cloud computing, it is critical to developing a business strategy and an accompanying technology operating model. A model of this type harmonizes processes for collaborative engagement between IT and business, thereby unleashing potential. CIOs Can Help CFOs Grasp the Cloud Business Case Cloud is a business priority, not an IT one. Because it is based on technology, the CIO must convince other C-suite members, including the CFO. The CIO may directly address the CFO's business priorities by demonstrating how cloud technologies improve business processes and overall enterprise performance. The CIO can also explain how using cloud-based solutions saves money by letting an external provider handle maintenance and hosting. With technical knowledge of data and infrastructure requirements, the CIO can help the CFO understand the dangers of cloud computing and how to solve CFO concerns like data governance and compliance. The CIO and CFO can collaborate along with CEO to derive better results from the benefits of cloud computing. Collaborate on a Deployment Plan Cloud technologies can be disruptive, whether they solve a problem or add new capabilities. Co-developing a deployment strategy that minimizes downtime, quickly trains employees on the latest technology, and establishes clear success indicators helps minimize interruption. The discussion should begin with an evaluation of the company's requirements, followed by comparing the various cloud technologies. The CIO can assess the company's current technological environment and identify new technologies that can cover the gaps. Understand the Financial Consequences of Cloud Computing The adoption of cloud technology will significantly alter expenses and cost structures. It will take the CIO's expertise to predict these changes. Cloud computing offers more than just long-term cost benefits. Also, CFOs must be aware of the initial costs and their possible influence on corporate efficiency and revenue. The CIO will understand a cloud vendor's service level agreements (SLAs), prices, and requirements to migrate legacy systems and train personnel on the new technology. Because the CIO will be actively monitoring the company's move to the cloud, they may advise the CFO on predicted cost and cash flow changes. This is crucial for the CFO, who must give Wall Street quarterly capital and operating expense predictions. Final Word In summary, the benefits of cloud computing can be reaped by applying high-level strategies. A flawless collaboration between the CEO, CIO, and CTO can transform a business's digital transformation journey into a successful venture. Right communication is critical during the cloud migration process. Employees should get this communication from C-suite executives to foster trust and assure compliance with governance requirements. FAQ How does cloud-computing help in the manufacturing industry? Cloud computing enables manufacturers to run their operations more intelligently, which is enabled through increased use of data analytics. Indeed, for the majority of manufacturers, the cloud is rapidly becoming the primary location for data storage, analytics, and intelligence. Why do manufacturers adopt the cloud? Cloud adoption is a strategic decision made by businesses to save costs, mitigate risk, and increase the scalability of their database capabilities. Cloud adoption varies from organization to organization, depending on the degree of acceptance. What are the 7 R’s of cloud migration planning? Refactor/re-architect, re-platform, repurchase, re-host, relocate, retain, and retire are the seven R’s in cloud migration planning.

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Top 5 Manufacturing Applications of Machine Vision

Article | October 20, 2021

Machine vision is becoming increasingly prevalent in manufacturing daily across industries. The machine vision manufacturing practice provides image-based automated inspection and analysis for various applications, including automatic inspection, process control, and robot guiding, often found in the manufacturing business. This breakthrough in manufacturing technology enables producers to be more innovative and productive to meet customer expectations and deliver the best products on the market. A renowned industry leader Mr. Matt Mongonce conveyed in an interview with Media7, As technology takes over and enhances many of the processes we used to handle with manual labor, we are freed up to use our minds creatively, which leads to bigger and better leaps in innovation and productivity -Matt Mong, VP Market Innovation and Project Business Evangelist at Adeaca. Why is Machine Vision so Critical? The machine vision manufacturing process is entirely automated, with no human intervention on the shop floor. Thus, in a manufacturing process, machine vision adds significant safety and operational benefits. Additionally, it eliminates human contamination in production operations where cleanliness is critical. For instance, the healthcare business cannot afford human contamination in some circumstances to ensure the safety of medicines. Second, the chemical business is prohibited from allowing individuals to come into touch with chemicals for the sake of worker safety. Thus, machine vision is vital in these instances, so it is critical to integrate machine vision systems into your production process. Machine Vision Application Examples To better understand how businesses are utilizing machine vision in production, we will look at five cases. Predictive Upkeep Even a few seconds of production line downtime might result in a significant financial loss in the manufacturing industry. Machine vision systems are used in industrial processes to assist manufacturers in predicting flaws or problems in the production line before the system failure. This machine vision capability enables manufacturing processes to avoid breakdowns or failures in the middle of the manufacturing process. How is FANUC America Corporation Avoiding the Production Line Downtime with ROBOGUIDE and ZDT? FANUC is a United States-based firm that is a market leader in robotics and ROBOMACHINE technology, with over 25 million units deployed worldwide. In addition, the company's professionals have created two products that are pretty popular in the manufacturing industry: ROBOGUIDE and ZDT (Zero Down Time). These two standout products assist manufacturers in developing, monitoring, and managing production line automation. As a result, producers can enhance production, improve quality, and maximize profitability while remaining competitive. Inspection of Packages To ensure the greatest possible quality of products for their target consumer groups, manufacturers must have a method in place that enables them to inspect each corner of their product. Machine vision improves the manufacturing process and inspects each product in detail using an automated procedure. This technology has been used in many industries, including healthcare, automation, and electronics. Manufacturers can detect faults, cracks, or any other defect in the product that is not visible to the naked eye using machine vision systems. The machine vision system detects these faults in the products and transmits the information to the computer, notifying the appropriate person during the manufacturing process. Assembly of Products and Components The application of machine vision to industrial processes involves component assembly to create a complete product from a collection of small components. Automation, electronics manufacturing, healthcare (medicine and medical equipment manufacturing), and others are the industries that utilize the machine vision system in their manufacturing process. Additionally, the machine vision system aids worker safety during the manufacturing process by enhancing existing safety procedures. Defect Elimination Manufacturers are constantly endeavoring to release products that are devoid of flaws or difficulties. However, manually verifying each product is no longer practicable for anybody involved in the manufacturing process, as production counts have risen dramatically in every manufacturing organization. This is where machine vision systems come into play, performing accurate quality inspections and assisting producers in delivering defect-free items to their target clients. Barcode Scanning Earlier in the PCB penalization process, where numerous identical PCBs were made on a single panel, barcodes were used to separate or identify the PCBs manually by humans. This was a time-consuming and error-prone process for the electronics manufacturing industry. This task is subsequently taken over by a machine vision system, in which each circuit is segregated and uniquely identified using a robotics machine or a machine vision system. The high-tech machine vision system "Panel Scan" is one example of a machine vision system that simplifies the PCB tracing procedure. Final Words The use of machine vision in the manufacturing business enables firms to develop more accurate and complete manufacturing processes capable of producing flawless products. Incorporating machine vision into manufacturing becomes a component of advanced manufacturing, which is projected to be the future of manufacturing in 2022. Maintain current production trends and increase your business revenue by offering the highest-quality items using a machine vision system. FAQ What is the difference between computer vision and machine vision? Traditionally, computer vision has been used to automate image processing, but machine vision is applied to real-world interfaces such as a factory line. Where does machine vision come into play? Machine vision is critical in the quality control of any product or manufacturing process. It detects flaws, cracks, or any blemishes in a physical product. Additionally, it can verify the precision and accuracy of any component or part throughout product assembly. What are the fundamental components of a machine vision system? A machine vision system's primary components are lighting, a lens, an image sensor, vision processing, and communications. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "What is the difference between computer vision and machine vision?", "acceptedAnswer": { "@type": "Answer", "text": "Traditionally, computer vision has been used to automate image processing, but machine vision is applied to real-world interfaces such as a factory line." } },{ "@type": "Question", "name": "Where does machine vision come into play?", "acceptedAnswer": { "@type": "Answer", "text": "Machine vision is critical in the quality control of any product or manufacturing process. It detects flaws, cracks, or any blemishes in a physical product. 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Engineering Intent is the World's Leading Provider of Enterprise Engineering Automation Tools and Solutions. We've been helping companies tame their complex product configuration solutions for decades.

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