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Summary

• Manufacturing plays a crucial role in global supply chains but has historically been plagued by inefficient and obsolete practices
• The pandemic has been a catalyst for accelerating digitization within the industry in categories such as design and engineering tools, operations software, robotics and automation, data and intelligence platforms, and cybersecurity

Background

Manufacturing is the process of converting raw materials into products that deliver value. For centuries, it has been a critical driver of innovation and growth globally. It makes up 16.5% of global GDP and is the largest consumer of natural resources. Manufacturing plays a key role and greatly impacts everyone's day-to-day routines. One does not have to look far to recognize the massive impact manufacturing has on daily interactions/life- from devices used to read this blog, clothes worn, food eaten, and cars driven.  Before the 18th century, most products such as clothing, food, and shelter were manufactured manually or with labor assistance animals. The labor market shifted with the introduction of steam-powered machines in the late 18th century, dubbed the most significant breakthrough for increasing human productivity. Steam engines empowered workers and businesses to scale their production of goods while also creating a culture shift focused on manufacturing products with quality, efficiency, and scale. Fast forward to the 21st century, we see technological innovations in cloud computing, advanced analytics, robotics, data collection sensors, cameras, and IoT devices. Today, the impact of the COVID-19 pandemic on the manufacturing industry is causing material and labor shortages and a shift in manufacturing operations. Technological innovation accompanied by the effects of COVID-19 has introduced the age of digital manufacturing.

The Breakdown

Components of digital manufacturing can be broken down into five categories: design and engineering tools, operations software, robotics and automation, data and intelligence platforms, and cybersecurity. All of these components are explored further below.

Design And Engineering Tools

A manufacturing process often starts at the design phase, which involves designers and engineers identifying a product's utility and creating a blueprint of it, most commonly done using Computer-Aided Design (CAD) models. Once the product design is finalized, the team proceeds to the testing phase. Manufacturing teams make an early prototype to test its performance during testing. This provides them a low-cost way of accumulating feedback along with the opportunity to reiterate the product. Only once the team is satisfied with the prototype's performance will manufacturing begin. The amount of time spent developing a product makes designing and prototyping a key component of digital manufacturing.

• CAD Design and Collaboration. The global CAD software market is currently a $9B industry. Designers and engineers create drastically different products from 20 years ago, such as 3D printed products. However, there have not been any major innovations around the software until recently. Change is occurring with the rise of software startups like Shapr3D and nTopology, which originated from the founders’ frustration with existing CAD software. On the collaboration side, communities of 3D designers are rapidly growing over the last couple of years through the likes of Thangs.
• On-demand Manufacturing. New marketplaces, which allow customers to access networks of machine and manufacturing shops on-demand, have enabled design and engineering teams to move rapidly through the testing phase. Major players in this space include Xometry, Fictiv, Zetwerk, and Fast Radius, who collectively garnered over $550M of VC funding.
• Additive Manufacturing (3D Printing). Additive manufacturing is several years into the Gartner Hype Cycle, where its technology has matured. Hence, a shift is occurring in the technologies’ target customers, from hobbyists and prototypers enabled by Glowforge, to larger-scale factories printing production-level goods enabled by ICON and Markforged.

Operations Software

Manufacturers use operations software to plan and execute projects from beginning to end while automating materials planning, production tracking, scheduling, and product lifecycle management. Material Requirement Planning (MRP), Manufacturing Enterprise Resource Planning (Manufacturing ERP), Manufacturing Execution Systems (MES), and Product Lifecycle Management (PLM) are some of the most widely used software in manufacturing.

• MRP Software provides control over the various factors that make up the final process and product come together. It involves determining what needs to be produced, its bill of materials, labor, and equipment costs, reordering inventory, scheduling production tasks for machines, and generating quotes. MRPs are fundamentally used to manage all events that drive production efficiency.
• Manufacturing ERP Software builds upon the existing functionalities of MRP softwares, with additional features used to manage operations such as supply chain management, finances, project management, and staffing to better serve the entire organization.
• MES Software is specifically designed to ensure quality and efficiency are built and enforced into the manufacturing process. An MES manages and aligns the execution of real-time, physical processes involved in manufacturing operations. To do so, the flow of work orders is coordinated with the production scheduling and ERP or PLM systems to enable visibility, control and optimal processes across the enterprise.
• PLM Software organizes all manufacturing information and processes at every step of a product or service lifecycle across globalized supply chains. It includes the data from bill of materials, CAD software, product requirements, engineering change orders, documents, and quality workflows.

For decades, the manufacturing operations software market has been dominated by incumbents such as Oracle, SAP, Plex, Siemens, and Forcam. This is gradually changing with new challenger startups such as Katana (MRP/ERP), Tulip (MES), and Propel (PLM) developing cloud-native products that are easy to use, and leverages modern analytics and API integrations.

Robotics And Automation

Labor shortages have plagued the entire manufacturing industry due to the COVID-19 pandemic. This creates a competitive nature amongst manufacturers to access a limited labor pool, driving up labor costs. At the same time, robotics is more affordable, enabling automations for all sizes of organizations. These two forces make it ideal to start deploying robotics and automation solutions in the factory. Robots in the industry come in all different shapes and sizes, including small-scale collaborative robot arms (OnRobot, Yuanda Robotics), larger solution robots (Formic, Veo Robotics), and specific use-case robots (Path Robotics, Gecko Robotics, Gizelis Robotics). Business models in the industry are undergoing innovations through a pay-as-you-go subscription and usage-based model. By innovating their business model, robotics companies can execute a faster distribution strategy as customers no longer need to worry about upfront costs and wait for lengthy budget cycles for capital expenditures.

Data Analytics And Intelligence Platforms

Outside of the labor shortages, the pandemic also saw manufacturing productivity drop significantly. Manufacturers need a new way to streamline operations through understanding their data. The quantity of data generated through MRP, MES, and IoT solutions in manufacturing is enormous, but many manufacturers have failed to utilize its potential. Manufacturing facilities use as little as 1% of their machine data productively. By taking advantage of innovations in advanced analytics, manufacturers are able to improve decision-making which boosts productivity, sustainability, and profitability. The Industrial Analytics Market was valued at $13.6B in 2020 and is expected to reach $36.73B by 2026, registering a CAGR of 18.03% from 2021-2026. Great analytics companies have been built over the past decades in every sector, revolutionizing operations through a data-driven approach. The same is happening for manufacturing technology where three unicorns, Uptake, Cognite, and SparkCognition are providing AI-based data analytics solutions in the factory. A key aspect of analytics is the monitoring of day-to-day working environment and operational activity. The average efficiency of manufacturing labor sits only at 60% as the tools to measure important metrics in the facilities are absent. The world embracing remote operations accompanied by advancements in vision algorithms and edge computing makes camera vision the perfect tool to measure what matters. Drishti currently leads the market in terms of funding. 

Cybersecurity

The digitization of manufacturing operations makes cyber threats impossible to ignore. According to a study done by Deloitte, they revealed that 48% of manufacturers surveyed identified operational risks, which include cybersecurity, as the greatest danger to smart factory initiatives. The magnitude of this threat makes cybersecurity a key component of digital manufacturing. The Global Industrial Cybersecurity Market size is expected to reach $22.8B with a CAGR of 7.2%. Several startups such as Claroty, Dragos, and Nozomi Networks, founded within a decade ago, are now tackling this hairy problem with innovative cyber defense solutions.

Final Thoughts

The manufacturing industry has come a long way from steam-powered machines to AI-powered autonomous machines. The various technological advancement over the past decade combined with issues caused by the pandemic is pressuring manufacturers worldwide to digitize, shift to the cloud, and automate processes, transforming into what we call a digital manufacturer.  Manufacturers and factories are the starting point of the supply chain. Therefore, Dynamo is actively looking to invest in supporting functions of this space. If you or someone you know is building a startup as such, reach out to us at hello@dynamo.vc.