The prioritization of innovation over process is hampering manufacturing
A deep disconnect between R&D and manufacturing is jeopardizing efforts to increase speed to market and achieve economies of scale for complex new technologies while harming safety and sustainability standards. The hand-off from product design and development to production creates significant risks as engineers prep the shopfloor to ramp-up the rate of production.
The failure to democratize engineering knowledge and bridge the gap between design and the first few articles being produced, to what is required for higher volume manufacturing means many production instructions are inaccessible on the shopfloor. The increasingly high cost of opening up this high-tech engineering knowledge to non-specialists also means that shopfloor workers are often being left without all the necessary knowledge required to complete their job without significant engineering oversite. The cost of not converting engineering knowledge into practical, accessible workflows often creates an additional risk that this invaluable engineering expertise could be lost to future retirements or resignations of key personnel. Failure to do so typically means manufacturing processes cannot be easily reproduced or standardized on a large scale, impeding companies from ramping up manufacturing at speed.
The failure to capture and communicate engineering processes and knowledge to non-specialists also prevents companies from streamlining and automating more of their manufacturing processes and adopting Industry 4.0 innovations. Crucially, there is a growing risk of defects creeping in once more non-specialists are brought in to accelerate the manufacturing process.
The disconnect between innovation and implementation
Manufacturing processes are perceived as an administrative cost rather than a competitive advantage while R&D is seen as the true money-spinner. This means companies often fail to invest in the cost of converting new innovations into practical manufacturing plans so that production instructions are often inaccessible to those outside the engineering department, preventing manufacturers translating complex concepts into mass-manufactured technologies.
For example, it is often prohibitively expensive to convert complex new designs into accessible, actionable manufacturing plans with clear steps expanded and explained, buyoffs added and data collection embedded at every stage. This impedes the necessary transparency and traceability needed to manufacture complex high-value technologies at speed and scale, this creates a dangerous disconnect between design and implementation.
Mutually incompatible point solutions and proprietary manufacturing systems further reinforce these data silos. A failure to share manufacturing insights widely is preventing companies from replicating and automating present manufacturing processes or harnessing data analytics to drive future process improvements. As a result, less than one in five manufacturers prioritize advanced analytics for either short-term savings or long-term structural improvements to costs and 61% have failed to scale data-driven production processes beyond a single product.
There is significant pressure to accelerate the speed to market which falls on the shoulders of overworked design and manufacturing engineers. This pressure, combined with the cost of continually making changes to the manufacturing processes, often means work instructions are frequently misaligned to the needs of production teams and can overlook real-world production requirements. A lack of communication during production means that engineers are missing vital shopfloor feedback from unexpected challenges to part changes which could drive more efficient production and smarter future designs.
As production is ramped, it is untenable to confine production knowledge to a small group of skilled engineers, and companies often have to bring in technicians of varying skill levels who may not have comparable engineering and product expertise. With the market being so hot in many industries and with massive pushes to develop workforces, ramp up of knowledge is often a luxury. We see companies trying to rapidly scale production by hiring non-specialist factory workers, sometimes from other industries and see them struggle to understand the intricacies at play. This is not only due to the tasks given but because they had been created by engineers for engineers.
Even worse, many changes are not centrally recorded due to the cost or challenges in ensuring traceability across manufacturing areas and product lines, resulting in these being left in issue systems or ticketing systems such as JIRA. While the change or non-conformance is tracked, it often does not control or prevent defective or untested parts from flowing through production, into the warehouse and shipping areas, and on to the real world. Any production errors or unanticipated changes can also cause a ripple effect across complex multi-tiered assembly processes, leading to costly delays or even dangerous defects going unnoticed.
Crucially, the accelerating pace of innovation and complexity of assembly makes it progressively harder for engineers to track and trace components to detect and correct errors at an early stage. Lack of visibility and traceability over manufacturing changes is causing excessive scrap rates and product recalls while creating safety and sustainability risks with new technologies. For example, the Space Shuttle Challenger Disaster was famously caused by engineering mistakes in designing two O-rings, while a recent tragedy involving a Red Arrow aircraft was caused by a single overtightened ejector seat bolt.
Scaling to high-speed, large-scale manufacturing
Accelerating speed to market for complex technologies will require companies to bridge the gap between innovation and implementation to create a mutually beneficial feedback loop from factory floor to design. Manufacturers need to embrace open, interoperable systems that enable data sharing across the manufacturing process from concept to completion. Everything from product design to process plans should be democratized and decentralized, creating collaborative processes continually adjusted to reflect operational realities. Process plans should be made accessible and configurable so that shopfloor teams can remotely adjust work instructions in real-time to make changes or correct errors.
Real-time inline collaboration and communication between engineering and operations creates agile manufacturing and engineering capable of adapting processes to ramp up production of complex new technologies. With centralized engineering, and a system optimized for change and execution allows for significantly easier reporting, analysis and machine learning. Live data on excessive downtime or unresolved defects could also help adjust maintenance procedures to quickly contain and correct defects and trace their cause, reducing safety or sustainability risks without excessive scrap rates. Engineers of various types can dig into all facets of the process to analyze risk and areas of opportunity.
Digitally integrating the factory floor with design would also create a digital feedback loop capturing and cross-fertilizing insights across projects to optimize future processes. Integrating processes into a single common planning solution to help centrally synchronize and optimize all manufacturing processes.
Pioneering manufacturers from high-tech industries including solar and aerospace are now adopting decentralized, data-driven planning solutions, that incorporate everything from real-time redlines to equipment alerts from the factory floor — but there is an urgent need for other emerging energy industries, such as wind, to establish better manufacturing processes now. This creates end-to-end visibility over changes and enables processes to be rapidly reconfigured to real-time manufacturing requirements.
Crucially, these companies are moving away from a narrow focus on R&D over the process and instead engaging shopfloor workers in everything from design reviews to approvals. The key to rapidly scaling from R&D to mass manufacturing is bridging the gap between engineering and operations, moving from linear to adaptable processes, and shifting from top-down to two-way information flows.
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