Industrial Engineering is System Efficiency Engineering. It is Machine Effort and Human Effort IE. 4 Million Page View Blog. 200,000+ visitors. (36,000+ pv, 25,500+ visitors in 2025.)------------------
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Azure Digital Twins now generally available: Create IoT solutions that model the real world
December 16 & 8, 2020
Sam George Corporate Vice President, Azure IoT
To really understand these intricate environments, companies are creating digital replicas of their physical world also known as digital twins. With Microsoft Azure Digital Twins now generally available, this Internet of Things (IoT) platform provides the capabilities to fuse together both physical and digital worlds, allowing you to transform your business and create breakthrough customer experiences.
One company pushing the boundaries of renewable energy production and efficiency is Korea-based Doosan Heavy Industries and Construction. Doosan worked with Microsoft and Bentley Systems to develop a digital twin of its wind farms, which allows operators to remotely monitor equipment performance and predict energy generation based on weather conditions.
Additional resources
• Learn more about Azure Digital Twins.
• Get started with Azure Digital Twins technical resources.
• Watch Azure Digital Twins demo video.
• Read Azure Digital Twins customer stories.
• Watch the Azure Digital Twins technical deep dive video featuring the WillowTwin solution.
• Learn how IoT and Azure Digital Twins can help connect urban environments.
• Learn more about Microsoft and Johnson Controls digital twin collaboration.
Enjoy the perfect overview. An exact 3D Live Digital Twin of your facility. Whether your house, office, factory or even a whole city (perhaps a space station?). It enables you to have your 3D model on your smartphone, tablet, PC or Mac and gives you access to all your data you desired to see and monitor in real-time.
Scalable and Modular
You can monitor any type of IoT Sensor, database and data stream, process, or workflow, up to real-time visualization of any kind of tracking and monitoring technology. You are always only one click away from the perfect overview you always desired.
Method and apparatus for producing a discrete droplet of high temperature liquid
Abstract
A method and an apparatus (10) eject on demand a discrete droplet (12) of liquid at a high temperature along a predetermined trajectory (18) by transferring a physical impulse from a low temperature environment to a high temperature environment. The ejector apparatus includes a vessel (26) having an interior (24) that contains a high-temperature liquid (14), such as liquid metal, Al, Zn or Sn. The interior includes an inlet end (30) that receives a thermally insulative impulse transmitting device (22) and a feed supply (34) of the droplet material, and a discharge region (56) having an orifice (16) through which the discrete droplets are ejected. An inert gas is feed through the inlet end and into the vessel to create an overpressure over the liquid so that as the overpressure is increased the droplet size is increased. A heater (70) heats the material contained within the interior. An impulse generator (20) is connected and imparts a physical impulse to the impulse transmitting device to produce an ejection pressure at the orifice to eject a discrete droplet of the high-temperature liquid. The impulse generator including a pulse generator electrically connected to a pulse amplifier that is electrically connected to an acoustic device, such as a loudspeaker.
A printer that produces objects from liquid conductive material is disclosed. In one embodiment, the printhead has a chamber for containing liquid conductive material surrounded by an electromagnetic coil. A DC pulse is applied to the electromagnetic coil, resulting in a radially-inward force on the liquid conductive material. The force on the liquid conductive material in the chamber results in a drop being expelled from an orifice. In response to a series of pulses, a series of drops fall onto a platform in a programmed pattern, resulting in the formation of an object.
Back in 2013 father and son Scott and Zach Vader developed an alternative additive manufacturing process, Magnetohydrodynamic (MHD) printing. They applied for patent in 2014. Acquired by Xerox in February 2019, Vader Systems’ technology uses wire feedstock in lieu of powder. Gravity feeds the molten metal from a tiny crucible into a nozzle and jets individual molten metal droplets on demand, creating dense metallic parts.
Low-Cost Material
The wire feedstock used in MHD can be as little as one fifth the cost of similar metal in powder form, making the process more cost effective and accessible for a variety of applications and industries. MHD also allows for greater control and geometric freedom in the production of parts by customising drop size, placement and spacing.
Using its drop by drop method, MHD can produce engineered lattice structures without the need for support materials – by overlapping the metal droplets to create an in-built diagonal support system. This helps create more complex structures without the need to remove supports in post production, helping to save time and costs. Geometric complexity can be achieved more easily and more cost effectively than traditional methods like die casting and even PBF, making MHD ideal for lightweighting in industries like automotive and aerospace.
MHD is currently is most suitable for aluminium and zinc alloys, as well as for aluminium alloys that are traditionally considered ‘unweldable’.
Research of Denis Comier - Earl W. Brinkman Professor of Industrial and Systems Engineering at Rochester Institute of Technology
Prof. Comier experimented with using MHD to print aluminium circuit board patterns onto flexible plastic substrates and, he reported that worked quite well. Drop off in conductivity was not there and there is good adhesion to the plastic. The feedstock is two orders of magnitude less expensive than silver nanoparticle inks, which could be a real game-changer in advancing printed electronics from research into industrial applications.
In molten metal jetting, where droplets of metal are jetted to 3D print a part, each layer may be traversed each successive layer with a normalizing grinding wheel or other leveling device such as a layer to level each successive layer, and/or the melt reservoir or printing chamber may be filled with an anoxic gas mix to prevent oxidation.
How does molten metal droplet jetting compare to traditional nanoparticle-based conductive inks?
This presentation was given by Denis Cormier from Rochester Institute of Technology at The Future of Electronics RESHAPED USA | Boston 2025 conference and exhibition
Molten Metal Jetting (MMJ) is an emerging metal AM process that offers low cost production
The potential advantages of metal additive manufacturing (AM) envisaged include the elimination of tooling costs, the possibility of on-demand manufacturing close to the point of need, near net shape production that reduces material consumption, and the ability to produce complex geometries that are impossible to make with conventional processes. But much of this potential has not been realized. The majority of production applications for metal AM have been limited to low volume, high-value parts for the aerospace and biomedical industries. Outside of those industries, it is often said that if a part can be CNC machined, then it will be faster and less expensive to CNC machine it than to make it via metal AM. The reasons for this are: Production grade metal AM machines often cost several multiples of the price of one CNC milling machine. Likewise, metal powder can be ten times or more expensive than bar stock used in CNC machining. Per-part print times can run hours to days, versus minutes to hours for CNC machining.
Laser Powder Bed Fusion (L-PBF) is the dominant metal AM process at the present time. l-PBF processes are well understood and are exceptionally well suited for making relatively small parts with intricate detail. The high cost of l-PBF machines and metal powder, coupled with low production speeds and environmental health and safety concerns explain why l-PBF has struggled to gain significant traction beyond the aerospace and biomedical industries. Binder jetting is likewise well suited for production of small metal parts with intricate detail. The equipment costs of binder jetting machines coupled with production-scale debinding and sintering furnaces are similar to those of l-PBF machines. Binder jetting likewise has similar concerns with the cost of metal powders and infrastructure needed to safely handle those powders.
Wire-feed Directed-Energy-Deposition (DED) methods (e.g., Laser Wire DED, Wire Arc AM and Electron Beam Wire AM) typically have lower per-part material costs than powder-based metal AM processes. The relatively high material deposition rates and robot motion stages make them well suited to produce very large parts. The tradeoff for high deposition rate with these processes is coarse feature resolution.
Molten Metal Jetting (MMJ) is an emerging metal AM process that uses on-demand ejection of molten metal droplets from a nozzle to produce metallic parts. There are multiple approaches to generating droplet ejection pressure pulses in MMJ printheads. Pressure may be generated via magnetohydrodynamic (MHD) , electrohydrodynamic (EHD), pneumatic, or vibrating piston jetting methods. Regardless of the droplet actuation method, each of these MMJ variants melts metal in a crucible prior to deposition. This means that any form of feedstock material may be used, including wire, rod, or even grain produced from ingots. For systems that use ingot as the feedstock material, the raw material cost of near net shape MMJ is even lower than that of CNC machined raw material. That represents a very important step towards tilting the scales from CNC machining with large material waste towards use of metal AM.
MMJ has been used to jet alloys of tin, alumimum, and Copper. . Reported droplet diameters range from as small as 50 µm to as large as 700 μm. Current state of the art commercially available systems claim deposition rates up to 199 using a drop size of 700 µm. There is obviously a tradeoff between deposition rate and feature resolution when selecting the diameter of the nozzle that droplets are jetted from. To increase deposition rates without sacrificing feature resolution, an array of individually addressable nozzles can be used.
Data-Driven 3D Printers: The Real Game-Changers for Manufacturing? Artificial intelligence and machine learning take additive to the next level.
Connected 3D printers can use collected data for artificial intelligence-powered automation. During each print job, 3D printers produce large quantities of data that are sent to and stored in the cloud. This data can help businesses make decisions about which parts to print and how best to print them, while improving the quality of print jobs.
Machine learning can optimize hardware, automatically enhancing 3D printers through software updates to increase printing speeds and improve resolution. AI can help businesses determine which parts, when produced in-house through additive manufacturing, will have the biggest impact on their bottom line. It can use digital catalogs of parts and detect which specific parts are the best candidates to be printed through various additive manufacturing techniques.
3D printers can use machine learning to automatically generate tooling jigs or fixtures to hold the parts they print. AI-based optimizations are used during the design stage of new parts — simulating how the digital design for a part, once printed, will perform under specific loads. AI is also employed in additive manufacturing to detect print failures (proactively pausing prints when needed), and to inspect parts as they’re being printed to ensure quality and conformance.
A Closed Loop
The same hardware out in the field is consistently learning, improving and getting smarter with every over-the-air update. As providers advance the quality of information collected during fabrication and build modes of collecting data about how each 3D printed part does its job on the field, manufacturing technology approaches a fully automated “closed-loop” printing process: One that can simply be presented with a real-world manufacturing problem to solve, and then design and build the part using the specific digital fabrication technology that makes the most sense given the defined time, cost, and performance constraints.
This smart, closed-loop automation of fabrication can substantially increase outputs and production speeds. And while additive manufacturing inherently streamlines the process of building parts, each savvy application of data collected by the printers can streamline distinct points within the additive manufacturing process.
Productivity of 3D Printing - Additive Manufacturing - High-speed 3D printing and the expanding material choice
3D Printer manufacturers are focusing on developing technologies that support higher production volumes, and materials that enable advanced AM applications. As a result, on the hardware side, the rise of binder jetting and multi-laser powder bed fusion for metals and vat photopolymerisation processes for plastics is occurring. Materials manufacturers are increasingly focusing on high-performance materials, including advanced alloys and composites.
The introduction of high-speed polymer AM technologies has significantly boosted the growth of 3D printing in dental. As estimated by the market research firm SmarTech, the AM dental and medical industry has topped $3 billion. Over 70% of dental labs in the US are predicted to own 3D printing technology by the end of 2021, with dental 3D printing becoming a $9.2 billion industry in the next five to seven years.
Metal powder bed fusion: Metal 3D printing encompasses many technologies, but one of the most matured among them remains metal Powder Bed Fusion (PBF). Key market players are launching solutions for automated and integrated production. They offer a high level of automation in a bid to maximise efficiency and reduce the amount of manual labour required. Thanks to these developments, laser PBF has found its way into many industries and applications. One industry that has been adopting metal PBF is aerospace. Today, metal PBF 3D-printed parts are powering crucial aircraft and spacecraft systems like engines. This is where the technology’s key capabilities — the production of complex parts with simplified assembly and less material waste — truly shine.
New launches of Additive Manufacturing systems with enhanced productivity (e.g. SLM Solutions, ExOne, Nexa3D, Voxeljet, EOS Systems), and a growing number of software companies in the field of AM boost the hope for applying AM technologies for a larger share of components. We at VTT & Aalto University are supporting productivity improvement of AM and have been developing and testing promising bio-based engineering materials produced from sustainable sources within the ValueBioMat project. We are focusing on advances in material science and innovation that are needed to get prepared for the future of AM, with productivity in line with sustainability.
BOFA International (Poole, UK) has developed an innovation that makes the exchange of filters in metal additive manufacturing processes safer, faster, and better for productivity. The laser powder-bed fusion process used in metal additive manufacturing needs filters. When new filters are needed for these systems, equipment has to be shut down and moved to a safe area for the saturated filters to be removed and replaced by operatives wearing full PPE—up until now. The new standalone AM 400 system’s technology enables the filters to be exchanged on site without risking a thermal event. The BOFA’s AM 400 filters are contained within a separate housing with a robust seal, enabling filter exchange to be completed quickly and safely without isolating the additive manufacturing equipment. This will reduce downtime of the equipment and increase productivity.
Application of Industrial Engineering Focus Areas in Additive Manufacturing
Productivity Science - Additive Manufacturing
Productivity science has to indicate process parameters that contribute to productivity improvement.
INFLUENCE OF PROCESS PARAMETERS ON THE MECHANICAL BEHAVIOUR AND PROCESSING TIME OF 3D PRINTING
Ramu Murugan, Mitilesh R.N, Sarat Singamneni
International Journal of Modern Manufacturing Technologies,
Vol. X, No. 1 / 2018 http://www.ijmmt.ro/vol10no12018/10_Murugan_Ramu.pdf
Ingrassia T., Nigrelli V., Ricotta V., Tartamella C. (2017) Process parameters influence in additive manufacturing. In: Eynard B., Nigrelli V., Oliveri S., Peris-Fajarnes G., Rizzuti S. (eds) Advances on Mechanics, Design Engineering and Manufacturing. Lecture Notes in Mechanical Engineering. Springer, Cham https://link.springer.com/chapter/10.1007/978-3-319-45781-9_27
Antonio Lanzotti, Marzio Grasso, Gabriele Staiano, Massimo Martorelli, (2015) "The impact of process parameters on mechanical properties of parts fabricated in PLA with an open-source 3-D printer", Rapid Prototyping Journal, Vol. 21 Issue: 5, pp.604-617, https://doi.org/10.1108/RPJ-09-2014-0135 https://www.emeraldinsight.com/doi/full/10.1108/RPJ-09-2014-0135
A Process Modelling and Parameters Optimization and Recommendation System for Binder Jetting Additive Manufacturing Process
Product Design Improvement for Productivity - Design for Additive Manufacturing
A design framework for additive manufacturing based on the integration of axiomatic design approach, inverse problem-solving and an additive manufacturing database
by
Sarath Renjith
MASTER OF SCIENCE
Major: Industrial Engineering
Program of Study Committee:
Gül Erdem Okudan Kremer, Major Professor
Michael Scott Helwig, Committee Member
Mark Mba-Wright, Committee Member
Iowa State University
Ames, Iowa
2018 http://www.imse.iastate.edu/files/2018/11/Chennamkulam-RenjithSarath-thesis.pdf
Process Improvement for Increasing Productivity of Additive Manufacturing
30 January 2018
To improve additive manufacturing productivity and lower cost per part, Renishaw has launched its latest system, the RenAM 500Q. Featuring four 500 W lasers, the compact machine will greatly improve productivity in the most commonly used platform size https://www.renishaw.com/en/pioneering-productivity-in-additive-manufacturing--43150
VERY HIGH POWER ULTRASONIC ADDITIVE MANUFACTURING (VHP UAM)
FOR ADVANCED MATERIALS
K. F. Graff, M. Short and M. Norfolk
Edison Welding Institute, Columbus, OH 43221
2010
To extend current ultrasonic additive manufacturing (UAM) to advanced materials, higher speeds and larger parts, it was essential to greatly increase the process ultrasonic power. EWI,
with Solidica™, several industry, agency and academic partners, and support of Ohio’s Wright
Program, have developed a “Very High Power Ultrasonic Additive Manufacturing System” that
greatly extends current technology. A key part was the design of a 9.0 kW “push-pull”
ultrasonic system able to produce sound welds in materials such as Ti 6-4, 316SS, 1100 Cu and
Al7075. The VHP system can fabricate parts of up to 1.5m x 1.5m x 0.6m. http://sffsymposium.engr.utexas.edu/Manuscripts/2010/2010-06-Graff.pdf
Industrial Engineering Economic Analysis of Additive Manufacturing
Optimal process parameters for 3D printing of dental porcelain structures
Hadi Miyanajia, Shanshan Zhanga, Austin Lassella, Amir Ali Zandinejadb, Li Yanga
Department of Industrial Engineering, J.B. Speed School of Engineering
Department of Oral Health and Rehabilitation, School of Dentistry
University of Louisville, KY, 40292
2015 http://sffsymposium.engr.utexas.edu/sites/default/files/2015/2015-132-Miyanaji.pdf
Human Effort Industrial Engineering of Additive Manufacturing
Industrial Engineering Measurements - Cost, Productivity and Time Measurement of Additive Manufacturing
Resource Consumption of Additive Manufacturing Technology
Nanond Nopparat, Babak Kianian
School of Engineering, Blekinge Institute of Technology Karlskrona, Sweden
2012
Thesis submitted for completion of Master of Sustainable Product-Service System Innovation (MSPI)
Blekinge Institute of Technology, Karlskrona, Sweden. https://www.diva-portal.org/smash/get/diva2:831234/FULLTEXT01.pdf
Technology Adoption
Partnering in Technology Development for Productivity Improvement
Volkswagen adopts the latest 3D printing technology, the "HP Metal Jet" process, which simplifies and speeds up metallic 3D printing. The process improves productivity by a simply staggering 50 times compared to other 3D printing methods for some components.
This process produces production-ready components for mass production applications in the automotive industry for the very first time. Volkswagen has closely partnered with printer manufacturer HP and component manufacturer GKN Powder Metallurgy in development for mass production use. The new process was demonstrated at the International Manufacturing Technology Show (IMTS) in Chicago this week.
85% Cost Reduction Due to Additive Manufacturing - $50,000 to $7,000.
10 sets of inlet booster rake for measuring air flow turbine engine test cells were made for $50,000 using a combination of welding, brazing, EDM, and other conventional medicines. The additive machining technology center made it for $7,000.
Huge Savings at Company Level - Honeywell Federal Manufacturing & Technologies
Honeywell Federal Manufacturing & Technologies has achieved huge cost reduction. As of FY 2018, they have printed more than 60,000 tooling fixtures for product testing and calculated $125 million in cost avoidance.
Design for Additive Manufacturing - Additive Manufacturing Industrial Engineering are Necessary for Effectiveness and Productivity
Huge Hybrid Manufacturing Machine is Ready to Start 3D Printing Construction Parts and Structures and Give Higher Productivity
31 JAN 2019
The machine will be tested to manufacture demonstrator parts, such as large cantilever beam structures, airplane panels and wind turbine parts. The machine and the process technologies are expected provide a more productive solution for the hybrid manufacturing of large engineering parts and deliver a projected 20% reduction in time and cost expenditure, as well as a target 15% increase in productivity for high-volume additive manufacturing production. https://adsknews.autodesk.com/news/huge-hybrid-manufacturing-machine-ready-to-start-3d-printing-construction-parts
Rather than building up plastic filaments layer by layer, a new approach to 3D printing lifts complex shapes from a vat of liquid at up to 100 times faster than conventional 3D printing processes, University of Michigan researchers have shown.
Michigan Engineering
January 11, 2019 https://news.engin.umich.edu/2019/01/3d-printing-100-times-faster/
SLA 3D Printing 100 Times Faster
________________
________________
MIT Researchers Developed FDM 3D Printing Head that makes Build Speed 10X
A. John Hart, an associate professor of mechanical engineering and director of the Laboratory for Manufacturing and Productivity and the Mechanosynthesis Group at MIT.
Screw mechanism for feeding the wire and a laser in the printhead to melt the wire more thoroughly were incorporated into the print head.
–Size of extrusion nozzle opening: ; The bigger the opening the more the material flow.
–Size of part to be printed. More volume, more time
–Part orientation on the build bed. X-Y orientations can usually be built faster than parts set up to build in the Z orientation.
–Complexity of part to be printed. Parts with many angles, curves and other geometric features will take longer to build than a straightforward box type shape.
–Material choice. In extrusion systems, every material flows at a different rate.
–Type of laser used in powder-bed systems.
–Type of material used in powder-bed systems. Plastics and metals will build at different rates.
–Required print resolution; Fine resolutions mean slower build rates.
–Part density. Fully dense parts can take longer to build than those with filler support.
The Ultimaker desktop 3D printer, gives its depositio rates as: With a 0.25 size nozzle, it is up to 8 mm3/s, a 0.40 nozzle it is up to 16 mm3/s, a 0.60 nozzle up to 23 mm3/s, and a 0.80 nozzle can deposit up to 24 mm3/s.
Professional 3D printer, the SLM Solutions 500HL gives deposition rates for its two-laser version as 55 cubic centimeters/hour, and its four-laser version as 105 cubic centimeters/hour.
Comparison of FDM, SLA and SLM
Fused Deposition Modeling (FDM)
Fused Deposition Modeling is the most widely used form of 3D printing at the consumer level. , FDM 3D printers build parts by melting and extruding thermoplastic filament, which a print nozzle deposits layer by layer in the build area. FDM works with a range of standard thermoplastics, such as ABS, PLA, and their various blends. The technique is well-suited for basic proof-of-concept models, as well as quick and low-cost prototyping of simple parts. .
Stereolithography (SLA)
Stereolithography was the world’s first 3D printing technology, invented in the 1980s, and is one of the most popular technologies for professionals. SLA uses a laser to cure liquid resin into hardened plastic in a process called photopolymerization. SLA parts have the highest resolution and accuracy, the clearest details, and the smoothest surface finish of all plastic 3D printing technologies. Material manufacturers have created innovative SLA resin formulations with a wide range of optical, mechanical, and thermal properties to match those of standard, engineering, and industrial thermoplastics.
Selective Laser Sintering (SLS)
Selective laser sintering is the most common additive manufacturing technology for industrial applications. SLS 3D printers use a high-powered laser to fuse small particles of polymer powder. The unfused powder supports the part during printing and eliminates the need for dedicated support structures. SLS is ideal for complex geometries, including interior features, undercuts, thin walls, and negative features. Parts produced with SLS printing have excellent mechanical characteristics, with strength resembling that of injection-molded parts.
Igor Yadroitsev, Ina Yadroitsava, Philippe Bertrand, Igor Smurov, (2012) "Factor analysis of selective laser melting process parameters and geometrical characteristics of synthesized single tracks", Rapid Prototyping Journal, Vol. 18 Issue: 3, pp.201-208, https://doi.org/10.1108/13552541211218117
Applied Industrial Engineering - IE in New Technologies
Industrial Engineers have to develop productivity science, productivity engineering and productivity management for new technologies. Are they doing it effectively? No industrial engineers are not doing it adequately.
AI and AI Agents are new technologies with application potential in many processes and systems. Industrial engineers have to learn those technologies and develop IE for those technologies.
Operations Function - The key areas where AI agents are making a significant impact
The Business Case
The adoption of AI is not just an upgrade to the technology stack; it is a disruption to operational processes and cost structure. With the real-time decision-making process, manufacturers are seeing improvements in operational efficiency that were very difficult to achieve with rules-engine-based automation.
The key areas where AI agents are making a significant impact include:
Autonomous manufacturing operations (Smart Manufacturing): AI agents can oversee entire production processes, ensuring robotic systems operate at peak efficiency and managing deviations in schedules. They can handle most real-time decisions, with human workers intervening only for issues requiring judgment.
Predictive maintenance: By continuously monitoring machine performance and sensor data, AI agents can predict equipment failures before they occur. This allows for scheduling maintenance. It is observed that plants significantly reduced unplanned downtime by up to 40% and cut maintenance costs by 20-25% using predictive maintenance agents.
Quality control and defect detection: AI agents can be used for real-time inspection, using machine vision, sensor fusion and anomaly detection to spot subtle defects that human inspectors might miss, especially in high-speed production. They can also adjust processes in real-time to correct issues, leading to a 30-50% reduction in defect rates.
Supply Chain Agents: AI agents can predict and react to supply chain disruptions by monitoring raw material availability, adjusting production schedules, optimizing resource use and even identifying alternative suppliers. They streamline logistics, forecast demand and manage inventory, helping to avoid bottlenecks and material shortages.
Energy optimization and sustainability: Manufacturers can significantly reduce energy waste as AI agents monitor consumption across machines and make real-time adjustments to minimize usage without compromising production targets. From our observations the implementation of AI tools at our plants, this can lead to energy savings of 15-20% and supports green manufacturing objectives.
Process automation and optimization: Beyond traditional robotics, AI agents enable cognitive process automation by improving decisions and workflows that were previously manual or rule-bound. They can dynamically adjust parameters like temperature and pressure in real-time based on historical data, ambient conditions and input materials, leading to less waste, fewer mistakes and consistent quality.
Workplace safety: AI agents can monitor environmental factors and safety metrics on the factory floor, predicting potential hazards and automatically triggering safety protocols—such as shutting down machinery or alerting workers—to ensure safe operations.
Intelligent manufacturing assistants: These agents integrate design intelligence into the engineering process, using generative design algorithms to explore product variants, analyzing customer data to recommend product tweaks and evaluating manufacturability before prototyping.
End-to-end automation: Advanced "super AI agents" can manage complex, cross-functional tasks across the entire manufacturing process, from material procurement and production planning to quality control and shipment. They integrate data from all aspects of the supply chain and manufacturing floor to ensure seamless automation.
A Dilemma of Marketing Managers - The First Customer Could be an AI Agent
“How do we remain visible and persuasive when the first ‘customer’ in the funnel is not a human, but an AI agent?”
McKinsey & Company
Our research estimates that by 2030, agentic commerce could orchestrate $3 trillion to $5 trillion globally, as AI agents increasingly influence discovery, decision-making, and transactions across categories.
As AI quickly becomes the first stop in the shopping journey in Europe and among industry leaders, the strategic question is shifting to: “How do we remain visible and persuasive when the first ‘customer’ in the funnel is not a human, but an AI agent?” https://mck.co/3Q7kKIM
In each branch of engineering the following three areas of industrial engineering are to be applied to increase productivity and reduce unit cost of output.
April 2026 Issue of Modern Industrial Engineering - Focus on Product Industrial Engineering - Value Engineering - DFMA - Design to Cost - Target Costing - Design for Value - Lean Product Development
Manufacturing Optimization for the Electronics Industry: How to Accelerate Product Development and Drive Engineering Efficiency with Instrumental Inc. on AWS
by Arun Santharam and Anna-Katrina Shedletsky on 30 MAY 2023
Help us to Reduce Your Cost of Electronics Manufacturing.
Electronic component procurement cost reduction program
Short Description:
In today’s electronics industry, companies face a common challenge. The main task is to reduce manufacturing costs without sacrificing product quality. Indeed, creating profitable products in our digital age is by no means an easy task. The only way to mitigate the difficulties is to delve into the specific steps of the process and use proven strategies to reduce overall costs.
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The two input MOSFET NAND gate used as an example. The first step in designing the NAND gate is to choose a model for the transistors. We chose a four terminal model that includes the effect of substrate
bias. This model and its defining equations are presented. There are many possible sets of designable parameters that could be used in designing the NAND gate, for example, the lengths and widths
of all the devices as well as the flat band voltages of the devices. We choose the flat band voltage, V _ , the
Ftf width of the bottom two transistors, W2~, (constrained to be the same) and the width of transistor T^ V^, as the designable parameters.
