A Guide to Connected Systems in Discrete Manufacturing

In every industry, manufacturers are under an urgent and growing array of competitive pressures: to be first to market with more innovative products; to deliver more personalized purchasing experiences; to improve quality in the factory and field; to deliver on time, every time. These competitive challenges must be met while controlling costs, contending with supply disruptions, and responding to demand fluctuations.

To address these demands, a wide variety of new and maturing software technologies are evolving, each intended to help realize the elusive promise of digital transformation. This dynamic places a heavy and complex burden on IT (Information Technology) teams, themselves under constant pressure to support the enterprise and its business goals. Where progress has been made, it’s generally been siloed, with work sequestered in a “field-of-action” approach with overlap between improvement initiatives. But the companies furthest along in their overall digital transformations have delivered important capabilities to their organizations through cross-functional alignment with the overall business strategy. Achieving those results required tying together data and processes across their strategic manufacturing support systems, including PLM, ERP, and MES.

This paper is intended to guide IT and business leaders toward that alignment. First, it will discuss how to properly identify the company’s collaboration needs based on business model and product complexity. Then, with needs effectively inventoried, it will introduce a proven, step-by-step process for delivering the right tools for integrating and configuring PLM, ERP and MES environments to meet them.

The result will empower R&D with dependable, real-time information, augmented by automation, to fuel fast and seamless global execution. These teams will be enabled to work concurrently, and more effectively than ever, with their counterparts in the factories, in logistics, and in procurement.

Global competition has intensified, and product innovation is only profitable if you get to the market first without compromising quality. How can you seamlessly integrate product and process changes (NPI (New Product Introduction) or New Product/Process Improvements) within this legacy IT landscape? It’s evident that manual handovers and data duplication in ERP, PLM, and MES systems degrade quality, add costs, and increase lead times and latencies, resulting in mismatching, and impairs meeting customer requirements due to poor traceability. It’s hard to scale the business in such an inefficient environment. Shop floor capacity can’t be doubled, for instance, without doubling the number of personnel inputting data.

Lack of transparency exacerbates change management issues. The manufacturing systems that exhibit these issues were designed for 30-year manufacturing veterans. But manufacturers today have a workforce comprised largely of three-year veterans, with 30% of frontline employees having less than one year’s experience. And this trend is accelerating even as products become more complex, and as rates of change are climbing.

Larger portfolios engender more quality issues. To keep making gains in quality, productivity, and sustainability, manufacturers urgently need to empower the new generation of front-line workers with the most effective product and process insights, when they need them, and where they’ll have the most impact. This will eliminate non-value-added time spent on finding information, and also provide frontline workers the tools to continuously identify, prioritize, analyze, and solve the choke points in their daily jobs. Only when they’re set up for success can these workers drive continuous improvement.

Weak governance requires frequent, redundant communication. Inefficiency reigns. To achieve those improvements - to reduce cost and improve quality - manufacturers must continuously fine-tune the operational efficiency of their products, processes, and resources, but also evaluate and optimize product and process design on an ongoing basis. The former usually has a bigger impact on labor costs and processing cost while the latter has bigger impact on materials cost. In general, 70% of the cost of any product is determined in the engineering stage.

Where systems are not integrated, engineers must do triple the work, entering the same data in PLM, MES, and ERP. The probability and size of quality problems are impacted by a lack of traceability. For example, manufacturers might have to recall a wide window of possible, suspect product because they didn’t know what configuration they were shipping on a given day. Too many sources of information result in low quality and low efficiency. Incorrect configurations are used because when a change takes effect it is not communicated appropriately. Products may then be built incorrectly, resulting in a defect that either the customer or manufacturer needs to catch as the product is prepared for shipment. Even with connected systems, these disruptions can seem to arise without warning.

Faced with any of these issues, how do you handle a modular configurable product throughout the value chain without automation across the network? How does the manufacturer find a supply alternative, while simultaneously addressing shifting business priorities, accelerating time to market, and improving quality? How can they ensure that the latest software version is available on the assembly line without changing the BOM? What’s the impact on testing? What if the factory is hacked? How are appropriate levels of cybersecurity and IP protection ensured?

There are real, measurable costs to these challenges, but perhaps the largest and most intriguing are the opportunity costs. How much better could the business do—put starkly, how much more money could be made—if these issues were resolved?