Digital Transformation in Manufacturing: Adapting to Industry 4.0 and Beyond
| By: John Butler, Contributing Editor, TECH B2B Marketing
Looking around the manufacturing industry today, one cannot help but take note of the increased presence of technology. Everything from material handling to cutting, shaping, inspecting, packaging, and palletizing can be done with some sort of automation and digital capability. Statistics related to sales and deployment of robotics, vision systems, and other automation equipment continue to achieve new highs. Yet despite the rapid introduction of digital solutions to aid manufacturers, plenty of manual and low-tech methods remain, particularly among more conventional sectors.
In response to increasing costs for labor and materials as well as consumer and market pressures for higher production quantities, shorter manufacturing times, and improved quality, many manufacturers are starting to integrate advanced digital technologies. Known more commonly as digital transformation, the process aims to enhance business decision-making, improve efficiencies, and lower costs over the long term.
In the age of Industry 4.0, the market landscape is in a perpetual state of shift and disruption, making it difficult for organizations that rely primarily on manual and conventional processes to keep up. The consequence is that inefficiency increases, productivity declines, waste and costs trend upward, and competitiveness suffers. To remain competitive, many manufacturers have started to leverage digital transformation. The shift to digital technologies is part of their strategy for long-term success.
Advanced digital solutions help make an organization more flexible and agile—able to respond more quickly to changes in market demand, to optimize supply chains with real-time visibility and predictability, and to improve their customer service through faster response times and more accurate order tracking. On the manufacturing floor, the benefits extend further, enabling automation, process and quality data tracking, and improved resource allocation, all with reduced downtime. With digital transformation—coupled with the Internet of Things (IoT), cloud services, machine learning, and artificial intelligence—manufacturers can see deep into their businesses, predict and prevent failures, and ensure a sustained level of operational resilience.
Adopting a Digital Approach
If your organization is beginning its journey into adopting digitization, the task can at first appear daunting. To avoid feeling overwhelmed and to maximize your chances of achieving successful outcomes, it is important to take small steps. Jonathan Weiss, CRO at Eigen Innovations, suggests that having clearly defined objectives and outcomes is key. He says, “Starting a project without a clear understanding of success or quantifiable business impact will almost guarantee failure when it comes to adoption.” Once the desired outcome has been defined, other considerations should center around ease of use, integration with existing technologies, and scalability.
With persistent labor shortages, costs for skilled labor continue to climb. So digital systems that are easy to use are attractive and advantageous as the barriers for operators come down, making these systems usable by a broader range of workers. Sophie Ducharme, marketing manager for Vention, sees ease of use as a major factor. She notes that Vention’s manufacturing automation platform (MAP) focuses on “simple, easy-to-use tools and solutions that enable those with a basic knowledge of implementing automation and manufacturing processes to design, automate, deploy, and operate digital systems.”
Overcoming Challenges and Obstacles
Digitizing manufacturing brings with it several barriers that must be successfully navigated. While many organizations can quickly grasp the benefits of adopting digital transformation technologies, elements such as large capital expenses, implementation costs, and complexity require consideration. The challenges don’t end there. At the personnel level, the availability of qualified workers, general resistance to change, and potential disruption to the status quo must also be factored in. Thirdly, when adding digitization to existing infrastructure, compatibility with and interoperability of existing or legacy systems may rank high among concerns. Davide Pascucci, founder and CEO of Bright IIOT, believes that upgrading a control system should usually be done in a way that preserves the same functionality as before. He says, “Much of the systems integration cannot be done in a vacuum, as interfacing the manufacturing floor with IT systems is not always a seamless process and requires coordination across the organization.”
Learning From Others
Often the best insights and advice come from those with experience, and their successes and challenges are great teachers. The importance of careful planning and consultation with all necessary stakeholders is top of mind for both Weiss and Pascucci. The planning process helps to identify potential trouble spots and provides an ability to anticipate and mitigate them as part of the overall business strategy for adopting digitization.
With digital transformation and automation being ongoing processes with an ever-changing landscape, it’s important that manufacturers remain agile and flexible so they can react quickly to unexpected changes. Ducharme sees manufacturing floors as living entities. Experience has taught her that “manufacturing systems are no longer designed for decade-long life spans.” Rather, “it is now common to see assembly lines and equipment upgraded, repurposed, or replaced every two to three years.”
Multiplying Success with Converging Technology
With the evolution of manufacturing technology, we’re seeing a fast-paced convergence of different technologies on and around the manufacturing floor, driving continuous progression and improvement. Machine vision, machine learning, and AI are further accelerating the transition into the digital era, enhancing data collection to further advance Industry 4.0 sophistication. Automated inspection has been used for many years to detect defects and failures, but Weiss explains that at Eigen Innovations, they pair machine vision systems that inspect products with process data. This shows not only where defects have occurred but why they occurred and, most importantly, how to prevent them in the future.
Bright IIOT sees vision systems as crucial to obtaining and providing inspection information and to identifying and eliminating product variances. Furthermore, vision systems can contribute to resource optimization as well. Where inspection can be reliably performed by machine, humans can be freed up for tasks that are higher value and more critical.
Vention’s Ducharme sees machine vision, machine learning, and AI as key for the establishment of smart factories. She echoes her peers’ thoughts on the value of combined data: “The combination of quality and process data enhances real-time quality control, predictive maintenance, data-driven decision-making, and overall efficiency.” Whether a manufacturer is small, medium-size, or large, advanced and innovative digital technologies are becoming must-haves to keep up with an ever-competitive global manufacturing environment.