Cost Optimization in Manufacturing with Digital twin

Bhagyashri Kambale | May 05, 2022 | 574 views
COST OPTIMIZATION IN MANUFACTURING
Digital twins appear to be beneficial in cutting expenses for many industries. A growing number of companies in the manufacturing industry, as well as healthcare, oil & gas, and other industries, are using digital twin features to better understand and respond to changing business conditions.

Digital twins can be used to save costs at numerous levels or segments of your business. Their use raises awareness of situations and helps businesses make better decisions. This technology has been applied to:

  • Change to standard care and conditional support in the railways
  • Use predictive care to foresee major impacts on the oil and gas industry
  • Monitor patients in real-time to improve comfort and avoid life-threatening scenarios

So, how do digital twin solutions assist manufacturers in cutting production costs?

Digital twins enable manufacturers to detect early mechanical defects, allowing for faster or cheaper repairs. Companies can save money by adapting to changing circumstances. For example, a corporation may automatically plan repairs to minimize performance impact.

Many companies use digital twins to cut expenses in various operating scenarios. In this article, we will look at situations to help recognize the benefits of digital twins.


Why Use a Digital twin?


Better R&D

The adoption of digital twins provides more effective product research and design. It also generates large amount of data about expected performance or results in the process. This data can provide insights that enable businesses to make necessary product refinements before initiating production.


Superior efficacy

The use of digital twins can be beneficial even after a new product has been put into production. This can help mirror and monitor production processes to achieve and maintain optimal efficiency throughout the whole manufacturing process.


Product end-of-life

As far as product lifecycle management is concerned, digital twins can assist manufacturers in determining what to do with products that have reached the end of their expected life and require final processing, whether through recycling or other means. They can figure out which product materials can be gathered with the help of digital twins.


Cost Optimization in Manufacturing using Digital twin


Transportation Cost Optimization

Digital twins are commonly employed in high-value rolling commodities like trains to improve fuel efficiency and competitiveness (i.e., predictable repairs). However, in the case of passenger automobiles, cost savings have been recorded (for example, improving security maintenance at passenger doors and train wheels).

When switching from conventional to state-based prevention in stock care, the rail transport operator claimed an average 10% savings.


Oil and Gas Cost Optimization

Companies frequently utilize digital twins to simulate and analyze functions like oil metals, pipelines, and processing plants. Among the business objectives supported by forecasting adjustments, machine learning, and other analyses are an increase in automated excavation or processing processes, a reduction in off-peak hours (FTE), and downtime, and the extension of the life of high-value assets.

The oil and gas businesses claimed that historical data forecasts for building repairs had been discovered near a substantial portion of their offshore oil production. This gave them time to lead security operations. They saved a week of unplanned unemployment and production expenditures. In less than a year, their digital investment has returned twice as much as before.


Supply Chain Cost Optimization

Businesses are increasing their investment in IoT and supply chain monitoring. Utilizing modern supply chain characteristics such as digital twins can assist businesses in achieving enhanced business results.

Monitoring the location and condition of high-value assets can assist in identifying anomalies that suggest an increased risk of theft. Additionally, this technology can be utilized to determine the location of assets for the purpose of recovery. While digital twins in many of these circumstances are straightforward – simply a location – in others, the supervised data may include natural characteristics such as the temperature inside the frozen container, generator fuel levels, or ways of detecting asset depletion or interruption.


Final Word

Is a digital twin necessary for your business? Yes, most certainly. By creating a comprehensive virtual picture of a company's processes, digital twins remove the element of uncertainty from decision-making. According to Gartner, 13% of organizations utilizing IoT already have digital twins in place, while 62% are either implementing or planning to do so. Hence, do not hesitate to deploy a digital twin in your organization, as it is worthwhile to invest in a digital twin that will help you lower overall production costs in the long run.


FAQ


Why is a digital twin necessary?

Digital twins are becoming vital in business. By making a digital copy of the physical assets of a product or service in an industry, digital twins help with data analysis and give people a way to check how things work before they happen. This way, they can develop a solution to any problem before it happens.


What data should be in the digital twin model?

The concept of the digital twin is based on three unique components: the physical product, the digital/virtual product, and the connections between the two.


How much does a digital twin cost?

According to some experts’ estimations, the cost of implementing a digital twin is $50,000 or less. Complex processes will necessitate a substantial investment and a lengthy implementation period to model.

Spotlight

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MANUFACTURING TECHNOLOGY, ADDITIVE MANUFACTURING

3 New Design Goals to Fuel Innovation Easily with Additive Manufacturing

Article | September 30, 2022

Stand out with long-term scalability with AM by fuelling innovation in the design process. Staying relevant has now become critical when it comes to additive manufacturing. It is, therefore, essential to make decisions by deep diving into the right people, processes, and technologies at the right moment to keep up the momentum when using AM processes. Better Product Designs with Design Innovation Framework for Additive Manufacturing Additive manufacturers have started using the product design innovation (DI) framework. It serves additive manufacturing part designs with increased - Proof of value (POV) - Helps your business stand out in the market with superior quality design. Proof of concept (POC) – Ensures that the design will function as intended. Proof of market (POM) – Defines the level of success of a design at scale for mass market production. Proof of impact (POI) – Using simulation to mitigate design failures and ensure that your designs last longer. As a result of the design innovation framework, additive manufacturing parts are manufactured faster and with better quality while lowering material costs. Furthermore, with more and more additive manufacturing companies implementing design innovation frameworks for their production, it is possible to tap into the opportunities of innovative product design at an early stage to give your production a competitive edge. Therefore, in the quest to grab an early market share in additive manufacturing for new, small and medium enterprises, the design innovation framework will play a pivotal role. Your product design, product research and development teams will implement the DI framework for the scalability of your additive manufacturing units. Fuel innovation and design thinking to produce innovative product design ideas with the goals and practices in the DI framework, as mentioned below. They infuse your designs with the design innovation framework to get quality manufactured products. Strategic Business Growth with AM Design to Fuel Innovation for Small and Medium Enterprises Fuel innovation in how you design additive manufacturing parts with strategic business growth. By keeping three goals in mind during the design process, you can use cutting-edge research in additive manufacturing design to help your business grow. Increase Speed: Create highly detailed intermediate manufacturing goods. As additive manufacturing is still in the transition phase, creating highly complex designs on a small scale is easy. But for large-scale AM production, intermediate goods like molds make it easy and quick to make intricate details. Build upon the existing DI (Design Innovation) process. Make use of designs from the design repositories and similar component geometry. Choose an orientation that does not need additional support. Save resources by preferring cellular structure over solid volumes. Make use of internal volumes to add more functionality. Print functional joints to save assembly steps and time. Standardize the assembly process to save production time. Use high-resolution STL files to reach your maximum design potential. Improve printability by scaling the artifacts and considering the resolution of the process. Manage Quality: Reduce residual stress to keep the parts from warping. Materials must be qualified and characterized to be micro-structured. Adhere to industry standards to get consistent, reliable, and repeatable outputs. While successful designs with strategic AM innovation can be beneficial to Create new products with AM. Create new business models with AM, AM helps to advance product design processes. Create new classes of AM technologies. Save Costs: Save costs by creating multifunctional parts. Choose a cheaper alternative material that satisfies the same constraints. Go for an economical assembly by manufacturing high-performing parts. Implement a cellular structure to reduce the quantity of material used. Innovate designs that bring down costs through accurate simulation of manufacturing constraints. Use composite material that satisfies the applied constraints. Risk Factors to Consider and Mitigate When Investing in AM The Risk of Data Leakage Cyber security is a critical component when storing design file data on the cloud and sharing it over the network. Getting a design file copied, stolen, altered, infected, or deleted causes a loss of time and sometimes money. Attackers ask for a ransom by putting a worm in your design file or blocking access. A highly private network with encrypted personal cloud connectivity and highly secure access control are the answers to mitigating the risk of cyber-attacks. Mitigating the risk is done with several measures. These include doing regular risk assessments, using a single design with no mistakes as a base for other design models, using advanced RFID tags to make products with AM, and practicing individual vigilance through awareness. The Risk of Poor Quality When outsourcing your manufacturing to an AM unit, the risk of low quality of the manufactured products is high. You cannot offer a warranty or guarantee when outsourcing production. Also, there is a risk that companies facing losses due to faulty products might want to claim for their losses. Quality improves when you give much attention to post-processing the manufactured parts. Leading Industries Using the DI Framework in AM: Aerospace Automotive Consumer products Energy Infrastructure Medical and pharmaceutical Food Sports Accessories Final Thoughts: Gearing up with innovation in additive manufacturing starts with three design goals. These include increasing speed, managing quality, and saving costs, which can help you achieve strategic business growth to scale for the long-term for business resilience. In addition, the DI framework for AM helps your large enterprise use progressive design thinking. So, now is the best time to invest into new ways to design products using design and management software for additive manufacturing.

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10 Best Features to Look for in an Additive Manufacturing Software

Article | September 20, 2022

The day is near when additive manufacturing (AM) will become production-ready, with many technological advancements in additive manufacturing software. Although taking care of manual post-processing is one of the challenges AM faces, methods to reduce it are on the rise with the help of better additive manufacturing software. Multilayer 3D printing revolutionises production, combining to fuel innovation. Let's find out what software features for additive manufacturing can help solve the problems that arise. How Does Additive Manufacturing Software Aid in the Resolution of Issues in Large Enterprises? For large enterprises, additive manufacturing software champions innovation to achieve long-term goals and resolve problems with these solutions. Sustainability in Manufacturing: A minimum wastage of material makes additive manufacturing sustainable. Therefore, achieve your goal of implementing sustainable practises quickly. Decrease Costs: Cut costs by automation, optimization, and simulation to help decrease costs at all stages of an AM workflow. Optimize Inventory: You can get rid of a lot of your inventory if you know exactly what material each part needs and how much of it you need. Easy Material Replacement: Simulate results for different materials and easily replace your material for printing as per availability. Combine multiple materials to strengthen parts and make them versatile. Generate Multiple Design Versions: The generative design approach allows you to generate multiple versions of a complex part subject to constraints. As a result, you reduce the guesswork and improve the quality quickly and efficiently. With AI designs in additive manufacturing software, you get progressive design innovation and development. As AM software aids large enterprises to fuel innovation in design implementation and follow the recent trends in additive manufacturing, AM processes such as binder jetting, metal additive manufacturing work and other types of additive manufacturing benefit from them as well. Explore the benefits of additive manufacturing for small and medium enterprises in our next segment which will cover additive manufacturing overview. Learn in-depth insights into why AM software are becoming a choice of medium sized businesses as well. Three Reasons to Use Additive Manufacturing Software To realize the full potential of additive manufacturing, good software plays a vital role in determining the quality of the output printed. Find out exactly how software for additive manufacturing could help your designs and your business grow. Automate: Automated light weighting, part consolidation, and generative design help unlock the scalability of your designs in terms of functionality and cost efficiency. Additive manufacturing software helps you achieve these efficiently. Optimize: Streamline the AM workflow using additive MES (manufacturing execution system) software. Increasing the printing process's efficiency helps reduce the time needed to print and improves the quality of the part manufactured and the machine utilization rates. Simulate and Test: Make your part design model subject to different constraints with the help of simulation using AM software. Reach excellence in additive manufacturing parts for real-life situations. Build a failsafe part using automated mathematical analysis. Using additive manufacturing software can help you overcome many challenges. However, while considering AM software, please note its shortcomings. The Big Challenge in Additive Manufacturing Software At each step of additive manufacturing, separate software is essential to perform different functions. AM software performs many critical functions, such as step-by-step design, printability checks, light weighting, adding support, and simulation analysis. However, a single software package does not exist that addresses all aspects of additive manufacturing. Software integration resolves this issue effectively and efficiently. Additive Manufacturing Software Functions for Large Enterprises For large enterprises, it is essential to get the accurate design of complex parts and manage the AM production workflow right. Additive manufacturing software brings both functions to the table. Learn how additive manufacturing fuels innovation in design. Features of Additive Manufacturing software for design and managing workflow are as under: Top Features of Additive Manufacturing (DfAM) Software: It is easy to nurture the design thinking process by arming with suitable DfAM software for medium and large enterprises. Their features are as follows: Topology Optimization: Using mathematical tools to simulate the material distribution of the part is topology optimization. Making changes in the material distribution can remove inefficient regions from the design. In addition, automated topology optimization helps quickly produce complex geometrical structures using DfAM software. Lattice Pattern Generation: Using additive manufacturing software, we generate 3D lattice patterns automatically. They significantly save costs by using a lower volume of materials and helping design multifunctional parts and structures. In addition, they reduce their weight and cost, making them flexible and stress-resistant. Generative Design: The power of generative design lies in designing to match all the design parameters, applying all constraints, and generating multiple design candidates quickly and efficiently. These include material type, shape, density, orientation, and more. This design evolves your part per your required parameters and expedites optimization. Automatic Light-Weighting: Applying light weighting techniques such as materials selection, part consolidation, conformal ribbing, lattice structures, and optimization of topology helps further bring down the costs. With DfAM software, the process is automatic and easy. Automated Part Consolidation: Creating a single part that can perform multiple functions saves space and costs, boosting efficiency. However, deciding whether consolidation can conform to other system components can sometimes be challenging. Find a way to solve this problem with the help of a feature in additive manufacturing software that automatically groups parts together. Stress, Heat, and Impact Simulation: Predict the part design's stress, heat, and impact-taking ability in the case of light weighting. Simulation helps test the part using different materials, keeping in mind their temperature, stress, and impact resistance. For instance, DfAM software tests a part before printing the prototype, utilizing this feature. Build Failure Prediction: Mathematical analysis-backed calculations of distortions and validations help in predicting building failures. A DfAM also helps predict building failures before they happen by calculating the efficiency over time. This makes the parts more durable. 3D Packing: Find the ideal shipping container and calculate its size, number, and maximum capacity using 3D packing technology. This automated software tool helps you efficiently send your shipments to your clients. Machine Parameters: Select the process parameters as per the part or product requirements. Apply different constraints to simulate the work using additive manufacturing software. Adjust them as per the desired characteristics in the output part using the software. Print Failure Prediction: Analyzing a designed model for deformation, cracks, stress, and growth is possible with software simulation. In addition, this data helps detect probable print failure. An end-to-end workflow automation solution using additive manufacturing MES software works in sync with your existing software. Learn about its features as below: Features of Good Additive Manufacturing MES Software: Order Management: Receiving, organizing, and processing orders for printing is excellent at order management. Part/file Analysis: The main tasks of part or file analysis are to look at the part or file's feasibility under different constraints and suggest ways to fix it. Production Planning: Production planning helps automate preparation for the production cycle. Instant Quotations: With built-in quotation management, create, approve, present, accept or reject quotations and place an order for part printing. Material and Inventory Management: It takes care of choosing the right material for the part and making sure that enough of that material is in stock to make it. Nesting: With nesting calculations, automatic space optimization on the print bed is possible Post-Processing Management: Remove defects after manufacturing using a streamlined post-processing management system. Quality Inspection and Management: Use the Quality Management System to remove possible distortions and deformations under constraints. Order Tracking and Traceability: Get the status of print order processing at all times with accurate tracking during the AM process. Analytics: Get a complete analysis of the data generated at each step of your AM workflow. If getting powerful software is not something you are considering at the moment, you can still welcome a host of new additions with the help of software integrations. Explore more about it down below. Use Software Integrations to Connect Existing Software: Link your existing software to your additive manufacturing software for seamless data sharing over the additive MES using software integration. For instance, connect existing AM workflows, 3D modelling simulations, import CAD files of models, send and receive purchase orders, and do much more with a one-stop MES solution. With the right integrations, you can add the features your software needs to stay current. When considering purchasing an AM software package, the initial, operational, training, and time required to learn it must all be calculated. For large enterprises, the reduction in inventory size and better accuracy with AM software bring down the cost of additive manufacturing production. Let us take a deep dive into the estimation of AM software. Estimation for Additive Manufacturing Software Setup and Operations: Depending upon the feature set of the additive manufacturing software, it might cost from $120/month/user to $25,000 annually or more. The significant influence is the implementation time and user-friendliness, like any other software for your business or enterprise. Several additive manufacturing and management software might have features that you may not need right now. However, upon scaling your business, they will become a necessity. You may want to consider software with supporting API integrations to smoothly transition from your existing software to advanced additive manufacturing software. As a result, you will reduce your cost of training the personnel while boosting their efficiency manifold. Additive Manufacturing Software's Future Scope Custom printing of complex geometrical structures with additive manufacturing is no longer restricted just to rapid prototyping. With the advent of volumetric additive manufacturing, it is now possible to print all the target points in the geometry simultaneously. Achieve this with the help of rotating the resin container with the guidance of a digital light projection system. In addition, this method can reduce some of the post-processing involved in an additive manufacturing production workflow to help make additive manufacturing more reliable and efficient. The future of additive manufacturing looks supremely promising with several applications of volumetric additive manufacturing. These include aerospace, medical, transportation, energy, consumer products and the like. In the future, revolutionary multifunctional parts will be created using automated part consolidation to optimize part designs like never before. Furthermore, using AI, accuracy is bound to improve. Conclusion: Building a resilient business for medium and large enterprises to unlock scalability is easy with a range of additive manufacturing software. Leveraging AM software saves turn-around time from researching to the production line with a stable and better design. It boosts ROI by streamlining your additive manufacturing workflows and cutting production costs using additive manufacturing software. Software integrations help enterprises stay current with all the features needed and introduced from time to time to make additive manufacturing practical. Using AI with AM software is becoming the norm for both medium and large AM companies that want to get a head start on the market.

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As a part of the Industry 4.0 movement, factory engineers are increasingly adopting some form of industrial Ethernet to interconnect the machines and other equipment implementing their production processes. Ethernet has been around in multiple forms for over 40 years. Most of it serves the IT community by interconnecting PCs and other equipment to a company LAN. Because of its flexibility, Ethernet has been adapted to many industrial uses.

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Innodisk Proves AI Prowess with Launch of FPGA Machine Vision Platform

Innodisk | November 24, 2022

Innodisk, a leading global provider of industrial-grade flash storage, DRAM memory and embedded peripherals, has announced its latest step into the AI market, with the launch of EXMU-X261, an FPGA Machine Vision Platform. Powered by AMD's Xilinx Kria K26 SOM, which was designed to enable smart city and smart factory applications, Innodisk's FPGA Machine Vision Platform is set to lead the way for industrial system integrators looking to develop machine vision applications. Automated defect inspection, a key machine vision application, is an essential technology in modern manufacturing. Automated visual inspection guarantees that the product works as expected and meets specifications. In these cases, it is vital that a fast and highly accurate inspection system is used. Without AI, operators must manually inspect each product, taking an average of three seconds per item. Now, with the help of AI solutions such as Innodisk's FPGA Machine Vision Platform, product inspection in factories can be automated, and the end result is not only faster and cheaper, but can be completely free of human error. Innodisk's FPGA Machine Vision Platform comes with 1GbE LAN, 4 USB 3.1 Gen1 ports, 2 M.2 slots, and a series of other expansion and connectivity options. Thanks to the platform's 0° to 70 °C operational temperature support, and optional industrial temperature support from -40° to +85°C, EXMU-X261 is tough enough for the harshest of industrial environments. In addition, EXMU-X261 features support for Innodisk's InnoAgent out-of-band remote management module, allowing the platform to be remotely managed from anywhere, even during a system crash or an in-band network failure. This is important for any automated system, as it allows for it to be completely unmanned, which further reduces manpower and maintenance costs. Customers can take advantage of AMD's Xilinx Kria K26 SOM's ability to quickly get applications to market thanks to EXMU-X261's full support for Innodisk's AI Suite SDK. The suite includes an FPGA Model Zoo, as well as Innodisk's in-house software solutions, such as iCAP (Innodisk Cloud Administration Platform), and iVIT (Innodisk Vision Intelligence Toolkit). iVIT for example, provides a deep learning environment for efficient development and deployment of "no-code-operation" solutions.

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