Did You Read about the Manufacturing Challenges for 2022?

Bhagyashri Kambale | December 08, 2021
MANUFACTURING_CHALLENGE
The new manufacturing industry outlook for 2022 is what businesses desire. Due to COVID-19, the sector has seen several ups and downs in recent years. But the industry overcame the most difficult situation by adopting innovations as their working hands.

But all this upgrading and digitalization in manufacturing isn't for everyone. Some manufacturers may struggle with this change, while others may not. So, taking into account all industry segments, we have compiled a list of potential manufacturing challenges for 2022.

“Many companies simply are not willing to change or think they are done once they make a change. But the truth is that technology, consumer demands; the way we work, human needs and much more are constantly changing.”

– Michael Walton, Director, Industry Executive (Manufacturing) at Microsoft

The summary of manufacturing industry challenges and industry outlook for 2022 are presented in the stats below.
  • According to the National Association of Manufacturers (NAM), four million manufacturing jobs will likely be needed over the next decade, and 2.1 million will likely go unfulfilled unless we motivate more people to pursue modern manufacturing occupations.
  • According to PTC, 70% of companies have or are working on a digital transformation plan.
  • According to Adobe, 60% of marketers feel technology has increased competitiveness.

The statistics show that while digitalization facilitates the process, it also poses several challenges that must be addressed in the coming years. Let's explore what obstacles manufacturers may face in 2022.

The Manufacturing Industry Challenges in 2022

The manufacturing business has had a difficult few years as a result of the current economic downturn, and 2022 may not be even that smooth. Thought, technology, and current trends make the operations of upscale manufacturers easier, but not everyone is on the same page.

Let's look at some of the manufacturing challenges that businesses will face in the next year.

Skilled Labor Shortage

The manufacturing industry is facing a workforce shortfall as a skilled generation prepares to retire. Industry experts say that by 2025, there will be between 2 and 3.5 million unfilled manufacturing jobs. As a result of the advancement of new technologies, manufacturing organisations are finding themselves with fewer personnel. They do, however, require individuals with a diverse range of abilities, such as mathematicians and analytic thinkers, to accomplish the tasks with precision.

Specific manufacturing tasks have been automated to save time and money. Industry has adopted machine sensors to capture large amounts of data. With this kind of innovation, the industry's job structure is changing and the desire to hire an untrained or trainable workforce is slowly fading in the industry. However, using augmented reality and virtual reality, manufacturers can easily train personnel for the job and save money.

Lack of Ability to Mine Data

Manufacturing is progressively using IoT. The majority of businesses have already installed or are planning to install Internet of Things machines. These smart machines let businesses collect data to improve production and conduct predictive maintenance. But getting data is a simple task. The difficult aspect is analyzing and aggregating data.

Despite possessing the machines, most companies lack the systems to analyze and retrieve the data recorded by the systems. In this way, the industries are missing a vital opportunity. The industry must improve data mining capabilities to make better decisions in real-time.

Using IoT for analytics and predictive maintenance is critical. Monitoring technologies can help the sector examine data quickly. It can also help predict an asset's maintenance period. As a result, the industry will move from replacement to predict and fix.

Self-service Web Portals That Is Extremely Detailed and Precise

Manufacturing businesses usually strive for on-time order delivery and optimum revenue. However, consumer self-service, which has been in the industry for a long time, has never proven to be a simple walk for clients. Clients are frequently required to pick up the phone and contact manufacturers in order to track their orders and receive delivery estimates. This is hardly the service one would expect from a manufacturer, even more so in today's digital era.

The term customers in manufacturing include partners, end-users, and subcontractors. These three clients have distinct requirements and concerns about collaborating with the manufacturer. Companies can better serve their customers if their partner and end-customer portals are linked to a central hub which we can mention as self-service web portals.

All of the information and updates they need about their orders will be available to them through this new system. They can track, accept and amend their tasks. They'll also use the self–service portal to contact the manufacturer.

In this way, manufacturers can better serve their customers. A system like this will ensure that all parties have access to timely information in a digital format.

Meeting the Deadline for the Project

Product launch timelines are extremely demanding, tight, and stringent. Every project in the assembly line is about cost, time, and quality. Ultimately, these projects are rigorous and well-controlled. Manufacturers who fail to meet deadlines risk losing millions in potential revenues and sales.

Due to rigidity and stringent control, companies are less able to change project scopes or make adjustments as projects develop. The majority of initiatives begin with a design commitment. As new facts or change criteria emerge, adjustment flexibility decreases. This can be aggravating for a team that expects high-quality results. Deadlines are always a constraint.

Effective Business Digital Marketing Strategy

An industry's key digital transformation challenges are driving leads, sales, and MRR through digital channels. Many manufacturing organizations struggle to efficiently use marketing channels like paid media, enterprise SEO, local SEO, content strategy, and social media. In our opinion, one of the most significant issues these organizations have is their digital experience, website design, and overall brand presentation. They can't ignore them if they want to keep enjoying the manufacturing revival.

Visibility of the Supply Chain

Manufacturers must respond to the growing demand from customers for greater transparency. In order to meet customer demand across the customer experience and product lifecycle, they must first understand that precise and real-time visibility throughout the supply chain is essential.

All details must be taken into consideration by the manufacturers. They must be aware of any delays in the arrival of products on the market. Keeping abreast of such developments would give them a leg up in terms of adjusting or rectifying the situation.

Final Words

Manufacturing industry challenges have long been a part of the industry. However, industry leaders and professionals have always confronted and overcome any challenges that have come their way. The year 2022 will also be a year of achievements, setting new records, and growth for the manufacturing industry, since it will be a year in which it will develop solutions to all of the aforementioned challenges.

FAQ


What is the future of manufacturing?

Manufacturers should start using AI, block chains, and robotics today. The combination of these new technologies will reshape manufacturing. A new workforce capable of augmenting these technologies is developing and will become the future of manufacturing.

How will automation affect manufacturing in 2022?

When applied properly, automation can greatly assist manufacturing. These benefits include shorter production times, faster and more efficient work than human labor, and lower production costs.

How is the manufacturing industry’s market likely to upsurge in the future?

According to BCC Research, the global manufacturing and process control market is expected to grow at a CAGR of 6.3 percent from $86.7 billion in 2020 to $117.7 billion in 2025.

Spotlight

Interconnect Devices, Inc.

Founded in 1979, IDI’s first decade reflected a commitment to the ATE (automated test equipment) industry. As IDI spring-loaded probes provided test engineers with the reliability they demanded, we asked the simple question: why not introduce our superior spring probe technology to other industries where reliable interconnect was in demand? So, in the early 1990’s, IDI introduced probe technology to semiconductor test engineers and designers of products where interconnect reliability was a top priority.

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Article | December 28, 2021

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Top Five Industries That Are Leveraging Additive Manufacturing

Article | October 20, 2021

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As the name implies, additive manufacturing is adding material to an item to create it." } },{ "@type": "Question", "name": "Is additive manufacturing the same as 3D printing?", "acceptedAnswer": { "@type": "Answer", "text": "Both terms are interchangeable. Additive manufacturing and 3D printing manufacture components by connecting or adding material from a CAD file." } },{ "@type": "Question", "name": "Which companies specialized in additive manufacturing?", "acceptedAnswer": { "@type": "Answer", "text": "American Additive Manufacturing, Forecast 3D, Sciaky, Inc., 3 Axis Development, Inc., Jonco Industries, Inc., Polyhistor International, Inc., and Caelynx, LLC are renowned companies for additive manufacturing in the United States of America." } }] }

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The Key Components of Industry 4.0 and Their Applications

Article | February 11, 2022

Industry 4.0 technologies, ranging from simulation to big data, have advanced significantly during the past few years. It is critical to gaining access to real-time outcomes and data that will propel the sector to new heights of lean success. Growing industry expertise and technological applications are making all cutting-edge technologies commercially available. However, the notion of Industry 4.0 is not straightforward. It comprises a wide range of technologies and is applied across a variety of circumstances. This article will explore some of the key components of Industry 4.0 and their application scenarios. All of them are critical components for industry to work smoothly, accurately, and effortlessly. Each individual component plays a unique role in the overall efficacy of Industry 4.0 technologies. Industry 4.0 Components Big Data and Analytics & Use Case Big data analytics is one of the core components of Industry 4.0. 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Eliminating Bottlenecks: Big data helps identify variables that may slow the operation’s performance and diagnose the issue at an early stage and eliminate bottlenecks. Predicting Demand: More accurate and relevant forecasts are made possible by visualizing activities beyond historical data through internal analysis (consumer preferences) and external analysis (trends and external events). This enables the business to predict demand, adjust and optimize its product portfolio. Proactive Upkeep: By recognizing breakdowns in patterns, data-fed sensors indicate potential problems in the operation of machinery before they become breakdowns. The system notifies the equipment in order for it to react appropriately. These are only a few of the applications of big data analysis in manufacturing systems; there are several others, including enhanced security, load optimization, supply chain meanagemnt, and non-conformity analysis.  Industrial Internet of Things (IIoT) & Use Case The next component in the industry 4.0 components list is IIoT. By virtue of its unique characteristics, the Industrial Internet of Things (IIoT) is creating massive changes in industrial applications. It greatly improves the operational efficiency and workflow of factories by monitoring assets and processes in real time. The IIoT presents several opportunities for entrepreneurs to improve their industry exponentially. “The Internet of Things is the game-changer for an overall business ecosystem transformation.” – Joerg Grafe, Senior Market Analyst, IBM IIOT Use Cases Predictive Maintenance: Maintenance schedules are established for machines and assets that run continually. Unplanned maintenance and failures often cost over $88 million a year. Predictive maintenance can help control these overhead costs. Sensor and device data allows predictive analytics systems to swiftly analyze current conditions, identify danger indications, send alerts, and initiate maintenance activities. For example, a pumping station motor in an ideal IoT facility may schedule maintenance if it detects irregularities in sensor data. This method saves money on routine and frequent maintenance. Asset Tracking: Asset tracking is designed to find and track valuable assets. Industries can track assets to improve logistics, maintain inventory, and identify inefficiencies or theft. Real-time asset tracking is vital in manufacturing. It may be used in warehouse and inventory management to keep track of the goods. This helps in finding the lost or misplaced goods in the warehouse. Industries with scattered assets may use IoT to track, monitor, and control them. Workplace analytics: More IIoT devices mean more workflow data for organizations. Data scientists can use analytics engines to find inefficiencies and offer improved operations. Location data analysis might also reveal warehouse inefficiencies. Remote quality monitoring: Sensors give faster and more cost-effective information about products or processes, leading to faster and more effective actions. Industry 4.0-enabled quality monitoring systems can also be obtained from the IIoT. Manufacturing factories can utilize IoT devices to remotely check material or product quality. It increases efficiency by allowing staff to verify many processes quickly. Similarly, real-time alarms make it easier for people to respond quickly, which lowers the risk of a failed product if left unchecked. Because remote quality monitoring is a novel concept, there aren't any ready-made solutions or services. Developing customized IoT technology to measure certain metrics can be costly and difficult. Cyber security & Use Case Industrial manufacturing has one of the highest data breach costs of any sector. The Ponemon Institute's 2019 Cost of a Data Breach Report estimates the average industrial breach at $5.2 million. In May 2017, the WannaCry ransomware assault crippled several manufacturing companies, forcing some to shut down plants for days. Overall losses were in the billions. “Cyber-Security is much more than a matter of IT.” ― Stephane Nappo Cyber security is vital for a safer digital zone on your factory floor or in your manufacturing business. It is one of the crucial 4.0 industry components. It's essential to be mindful of the weaknesses while modernizing manufacturing. The largest risk in an open factory environment with widely distributed partners and operations is an incident that disrupts operations. No manufacturing company, or any organization, for that matter, should pursue digital transformation without including cyber security in every step and decision. Cyber Security Use Cases Analyzing network traffic to detect patterns indicative of a possible attack Detect harmful activities or insider risks Response to incidents and forensics Manage the risk associated with third- and fourth-party vendors Identify data intrusions and compromised accounts Risk management, governance, and compliance Threat hunting is a technique for identifying signs of attack Additive Manufacturing & Use Case Additive manufacturing is a set of manufacturing processes that create a final product by layering material. Additive manufacturing reduces production and supply chain costs by enabling the rapid creation of large quantities of parts. It eliminates stock and the requirement for molds. Initially, 3D printing was utilized for prototyping and is still the rule. However, 3D printing technology has advanced; it is now more inventive than ever before. “3D printing is going to be way bigger than what the 3D printing companies are saying.” – Credit Suisse Additive Manufacturing Use Cases Parts for New Products: Porsche is 3D printing aluminum pistons for the Porsche 911 G2 RS engine. The improved product was made feasible using generative design software, aluminum powder, and 3D printer improvements. General Atomics Aeronautical Systems has teamed up with GE Additive to print a NACA inlet. The component is made via laser powder bed fusion. Parts for the Aftermarket: Aftermarket components are defined as non-OEM (original equipment manufacturer) replacement parts. Thyssenkrupp and Wilhelmsen Marine Products have teamed up to offer 3D printed replacement components. With aged ships, the maritime sector frequently needs hard-to-find, costly, and time-consuming spare components. 3D printing spare parts near to the source reduces lead times and shipping costs. Jigs, Fixtures, Molds and Tools: Jigs, fixtures, molds, and tools are essential in manufacturing. When one of these fails, a plant's downtime is prolonged. Jabil, a manufacturing services firm, has adopted 3D printing. They no longer have to wait weeks for tools or components. They can now produce tooling, fixtures, and manufacturing aids in-house in days, speeding up new product launches and increasing customer satisfaction. Simulation and Virtualization & Use Case Simulation in manufacturing systems is the process of using software to create computer models of production systems for the purpose of analyzing them and obtaining valuable information. According to syndicated research, it is the second-most popular management discipline among industrial managers. “Simulation is the situation created by any system of signs when it becomes sophisticated enough, autonomous enough, to abolish its own referent and to replace it with itself.” - Jean Baudrillard Simulator software lets businesses try out new technologies and principles in a risk-free, virtual setting so they can make sure they're making the right investments. Simulation Use Cases Interoperability: The simulation showed how downstream work stations may use extra location data to more efficiently choose and organize work batches to satisfy client demand. Information Transparency: Using sensor data, we may construct a virtual replica of the physical world, such as a manufacturing plant or contact center. This technology allows an operator to visually evaluate and certify products. Technical Assistance: Simulating the use of Automated Guided Vehicles (AGVs) to accelerate traditional production and manufacturing processes. Additionally to substitute physically hard jobs such as stock moving is becoming increasingly popular. Due to simulation's ability to capture the process time variation, it is an effective tool for validating critical design parameters. For example, the number of AGVs to purchase, the overall benefits to throughput, maintenance planning, and track layout. Decentralized Decisions: In a high-mix, high-volume production plant, a simulation is performed to examine the feasibility of increasing a palletizer's storage capacity in order to 'rack-up' a series of basic tasks for overnight processing while reserving more complex processes for staff hours. The simulation lets you try out a large number of test scenarios, including worst-case scenarios in which the machine becomes stuck near the start of its overnight operation. Final Word Industry 4.0 is a solution bundle for manufacturers to improve their manufacturing, inventory, and supply chain management. The key components mentioned above are only a few from an extensive list. There are more industry 4.0 technologies to include in the list, including digital twins, cloud, virtualization, robots, augmented reality, artificial intelligence, and more. Many of these technologies are now accessible to make future forward smart factories a reality today. Know about the uses of each component and learn how to integrate it into your digital manufacturing. FAQ What is industry 4.0 also called? Industry 4.0 is also known as IIoT or smart manufacturing. It combines physical manufacturing and operations with smart digital technologies such as machine learning, and big data to create a more holistic and linked environment for manufacturing and supply chain businesses. Why is Industry 4.0 needed? Industry 4.0 technologies help you control and optimize your production and supply chain operations. It provides real-time data and insights to help you make better business decisions, eventually increasing the productivity and profitability of your company. What are the four core components of industry 4.0? In an attempt to define Industry 4.0 concept, German researchers developed a list of industry-defining components. They are: cyber-physical systems, IoT, Internet of Things, and smart factories.

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How Collaborative Robots Are Revolutionizing the Manufacturing Industry

Article | December 10, 2021

A new form of robot is entering manufacturing plants all around the globe. Instead of being locked away in their own work cell, collaborative robots work side by side with their human counterparts. Together, they form the manufacturing crew of the future. Collaborative robots, or cobots, are more flexible, easy to use, and safer than industrial robots. Instead of ending up abandoned in a corner, they are proving to be serious expansions of production capacity leading to better ways of creating superior quality products. 1.1 A New Breed of Bot Cobots are a new type of automation product with their own ISO standards for safety and usability. For a robot to qualify as a cobot, it has to be used for tasks of a collaborative nature while sharing all or part of its reach space with human operators. So it is not the product alone that classifies it as a cobot. Industrial robots must be expertly programmed for one specific job along the production line. This requires hard line coding and endless tweaking and testing, which together with other factors make for a sizable upfront investment. Not so with collaborative robots. Cobots may look similar to traditional robots in some ways, but they are much easier to install and program. This foregoes the need to cooperate with a robotic integration service. Their lightweight and friendly form factor lets manufacturers conveniently relocate them on the shopfloor from one project to another. This renders the robotics technology perfect for a data-driven, Industry 4.0 work environment. Cobots can side with traditional machinery and additive manufacturing equipment, aided by artificial intelligence and cloud connectivity while embedded in a networked environment rich with smart sensors and mixed reality interfaces. 1.2 A Unique Blend of Benefits Because it is fairly straightforward to reprogram a cobot to various tasks, they are perfect for high-mix, low-volume work to meet the rising demand for ultra-customized products. They can also do multiple tasks in unison, such as alternatingly loading a machine and finishing parts from the previous cycle. Here are some other advantages in addition to flexibility: • Low investment. Cobots typically cost a fraction of the price of an industrial robot, but they offer much lower payload and reach. ROI is typically one to two years. • Safety. With rounded surfaces, force-limited joints, and advanced vision systems, cobots are exceptionally safe. This reduces the risk of injury due to impact, crushing, and pinching. Driverless transport systems are wheeled mobile robots that immediately halt when their lasers detect the presence of a nearby human being. • Accuracy. Cobots score well on accuracy with 0.1mm precision or well below that. While they do typically sacrifice speed, dual-mode cobots can be converted to fully-fledged tools of mass production that run at full speed in their own safeguarded space. • Easy to program. Many brands offer user-friendly programming interfaces from beginner to expert level. This reduces the need for continuous availability of expensive and scarce expertise while giving current employees an incentive to upskill. And because they can be deployed within hours, cobots can be leased for temporary projects. • Research. Small processing plants, agile start-ups, and schools can invest in cobots to experiment with ways to automate processes before committing to full automation. 1.3 Cobot Activity Repertoire Cobots are perfect candidates for taking over strenuous, dirty, difficult, or dull jobs previously handled by human workers. This relieves their human co-workers from risk of repetitive strain injury, muscle fatigue, and back problems. They can also increase job satisfaction and ultimately a better retirement. The cobot’s program of responsibilities includes: • Production tasks such as lathing, wire EDM, and sheet stamping. • Welding, brazing, and soldering. • Precision mounting of components and fasteners, and applying adhesive in various stages of general assembly. • Part post-finishing such as hole drilling, deburring, edge trimming, deflashing, sanding, and polishing. • Loading and unloading traditional equipment such as CNC and injection molding machines, and operating it using a control panel to drastically reduce cycle times. • Post-inspection such as damage detection, electronic circuit board testing, and checking for circularity or planarity tolerances. • Box-packing, wrapping, and palletizing. • Automated guided vehicles (AGVs) and autonomous mobile robots (AMRs) assist with internal transport and inventory management. 1.4 No-Code Programming While an industrial robot requires the attention of a high-paid robotics engineer, anyone with basic programming savviness can install and maintain a collaborative unit. Brands are releasing more and more kits for quick installation and specific use cases. Instead of being all numbers and line-coding, current user interaction is exceptionally people-focused. At the lowest skill level, lead-through programming lets operators physically guide the cobot’s end-of-arm-tool (EOAT) through the desired motion path, after which it will flawlessly replicate the instructed behaviour. It is also possible to enter desired waypoints as coordinates. At the highest level, it is of course still possible to have full scripting control. An intermediate step is visual programming interfaces. These let users create blocks of functionality that they can string together into more advanced action sequences, while entering the appropriate parameters for each function such as gripping strength, screwing tightness, or pressing force. These UIs come in the form of in-browser or mobile apps. Based on a 3D-CAD model of the machine and its industrial environment, a digital twin of the cobot can simulate and optimize its operations, for example to prevent collisions. It also lets operators remotely monitor and adjust the machine while it’s running. All the while, back-end artificial intelligence can do its analyses to find further efficiency improvements. 3D models of the to-be-manufactured product can be imported for edge extraction of complex surfaces. These will then be converted into the cobot’s desired movement trajectories instead of tedious manual programming. This makes them feasible to implement for highly dexterous tasks like welding curved hydroformed metal parts or sanding and polishing the most intricate of 3D printed geometries. Interfacing directly with the robot is becoming increasingly human-centered as well. Future cobots will respond to voice interaction as well as touch input, eradicating the screens-and-buttons paradigm of current devices. Some brands are giving the cobot a face with emotional expressions, hoping to lower the barrier to adoption. The upcoming generation of cobots can even respond to body language, as well as show its intentions by projecting light to where they are about to reach or move next. 1.5 A Human World Ultimately, the objective of any company is to create value for people. It is not an option to completely remove humans from the shop floor in an attempt to stay at the forefront of innovation. Attempting to leap to full automation and the utopian “lights-out factory” does not work anyway, as automotive giants such as Ford, Chrysler, GM, and Tesla can testify. A significant portion of human employees will indeed need to give up their roles. On the other hand, improved productivity levels open up space to retain personnel and uplift them to more creative, managerial, analytical, social, or overall more enjoyable jobs. For certain tasks, humans still need to be kept inside the manufacturing loop. For example: • Complex assembly routines and handling of flexible components. • Large vehicle subassemblies contain many variable components and require more hand-eye coordination than one cobot can handle. Humans are needed to make sure everything lands in the right position while the cobot provides assistive muscle power. • Fashion, footwear, jewellery, art pieces, and other products where creation borders on artistry rather than mechanical assembly require the aesthetic eye of humans. People are also needed to spot aesthetic deficiencies in custom one-offs in order to correspond with customers before finishing the production batch. • While intelligent automation software can spot bottlenecks in efficiency, humans are required for creative problem solving and context-awareness to make decisions. A spirit of flexibility and innovation is just as important as the accuracy of perfect repetitions. 1.6 Mission: Install a Cobot Cobots have numerous advantages over industrial solutions or people-only workspaces. They enable faster, more precise, and more sophisticated operations while reducing downtime and maintaining employee satisfaction. Low-voltage operation and reduced material waste fits with sustainable innovation and corporate social responsibility programs. Many companies are reporting surges in production capacity and staff generally experience the presence of cobots as favorable. For example, industry leviathans like BMW and Mercedes-Benz are reaching the conclusion that in many parts of the production process implementing a cobot has been the right decision. Connecting all parts of the production line with full automation solutions is a pipedream. It works only when all steps are perfectly attuned, and in reality this never happens and one misstep can be catastrophic. Whether to hire a human, a robot, or a co-robot is a complex and ever-more pressing decision. Statistical process control is paramount for large organizations to make unbiased data-driven decisions. Determine the key performance indicators, then find the most critical bottlenecks and major opportunities for leaps in production efficiency, product quality, or staff unburdening. Talk to employees for their insights and probe their level of skill and enthusiasm needed for working with their new artificial assistants. Digital transformation should be an exciting shift in the organization and its people, so apply new technological advancements only where it makes sense. Despite common beliefs about robotization, the cobot is an entirely separate product category that can be a surprisingly plug-and-play solution for simple tasks, with programming apps becoming increasingly intuitive. A cobot’s flexibility makes it perfect to run early experiments to help companies find its best spot on the factory floor. Its unbelievable precision, consistency, and level of control generally can make a strong first impression on customers. Not only can cobots increase production capacity while reducing idle time and cycle time to accelerate manufacturing across many vertical markets, but they also enrich the work environment resulting in happier and more involved employees. For many companies, a cobot can be the next logical step in their digital transformation.

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Interconnect Devices, Inc.

Founded in 1979, IDI’s first decade reflected a commitment to the ATE (automated test equipment) industry. As IDI spring-loaded probes provided test engineers with the reliability they demanded, we asked the simple question: why not introduce our superior spring probe technology to other industries where reliable interconnect was in demand? So, in the early 1990’s, IDI introduced probe technology to semiconductor test engineers and designers of products where interconnect reliability was a top priority.

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