The Comprehensive Guide to Product Lifecycle Management

The differences between CAM systems no longer come from what they can do, but from how efficiently, predictably and automatically production runs with them.

When looking for a CAM solution, the discussion often focuses heavily on technical details. Does the software support milling, turning or multitasking machines? Are postprocessors available? Is the user interface easy to learn?

These are still relevant questions, but to be honest, they no longer differentiate solutions. Almost all modern CAM systems can handle the same basic tasks. The real question is no longer what the software can do, but how efficiently and predictably production works with it.

In many machine shops, CAM programming is still largely an individual effort. This is actually a fairly universal challenge across many industries. An experienced programmer can get things done quickly, but at the same time dependency on that person increases. Knowledge stays in people’s heads and does not scale. This becomes visible when workload increases or new people join. In a modern environment, this should no longer be an acceptable starting point.

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Guided processes

CAM software should enable programming to become a guided and repeatable process, not manual work. When geometry is automatically recognized and machining strategies are selected based on rules and “company best practices”, programming shifts from an individual task to an organizational capability. At that point, we are talking about productivity, not just a tool.

In practice, the software recognizes typical features in the model, such as holes and pockets, and automatically assigns tools and cutting parameters based on predefined practices. PMI data, such as tolerances and surface finish, guides the selection of the correct machining strategy. For example, tighter tolerance holes can be finished by reaming to achieve the required tolerance range. This reduces manual work and shifts the programmer’s focus to areas where automation does not yet apply or is not sufficient.

Another often underestimated topic is the relationship between CAD and CAM. In many companies, these still operate separately, even though they should not. When models are transferred between systems, gaps are introduced, and data translations can degrade the model. Changes do not update, errors occur and time is wasted. When CAM operates in the same environment as design, the situation changes significantly. Programming can start before the design is finished, and changes update automatically. This is not just a convenience, it directly impacts lead times and error rates. In practice, it is about doing things right once instead of fixing them multiple times.

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The importance of simulation

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Simulation is another topic that is often mentioned, but its importance is not always fully understood. Simply visualizing a toolpath does not show what the machine will actually do. If simulation is not based on NC code and real machine kinematics, uncertainty remains. A modern CAM solution should allow the program to be run digitally before it is sent to the machine. When simulation is based on postprocessed NC code and can be taken all the way to controller logic level, the digital and physical worlds start to match. Collisions, errors and even cycle times can be evaluated in advance. In practice, this means that you no longer test on the machine, but production can start as it was planned.

Postprocessors have traditionally been one of the biggest concerns, but at the same time their importance is often underestimated. The discussion easily focuses on CAM software features and what can be programmed. In reality, CAM is only as good as its postprocessors. Programming can be smooth and the interface easy to use, but if the postprocessed NC code does not control the machine correctly, the program itself has no real value.

In the worst case, a poor or incorrect postprocessor leads to wrong machine movements, lower quality or even tool and machine damage. For this reason, the postprocessor should not be seen as a single technical component, but as a critical part of the whole manufacturing process. The key is not only that postprocessors are available, but how they are managed, developed and validated as part of the overall solution.

This is where NC simulation becomes especially important. When the postprocessed code can be validated digitally with machine kinematics and even controller logic, it is possible to ensure that the program works correctly before it reaches the machine. This means validating not just the toolpath, but the entire machining process. At its best, this speeds up the commissioning of new machines and significantly reduces production risks.

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The number of axes

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When discussing technical capabilities, the conversation still often turns to the number of axes. It is worth stating that modern CAM solutions cover different machine types and machining methods quite broadly, from basic milling and turning to advanced multi-axis and multitasking machines. However, this is no longer the first discussion that should be had.

Whether the software supports 5-axis machining, how many channels can run simultaneously and so on are valid questions, but they do not define everyday efficiency. Most machining is still 3-axis or 3+2 machining, and continuous 5-axis machining is used where it truly adds value. What matters is not what is possible, but how easily and reliably the most common tasks can be completed. If programming requires a lot of manual work and adjustments, errors will increase. When the system supports and guides the user, the result becomes more consistent and predictable.

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AI is coming

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Artificial intelligence is the latest addition to CAM discussions, and it is no longer just marketing talk. Its value is not in doing everything for you, but in supporting the user at the right moments. When the system learns from user behavior and suggests next steps or parameters, work becomes faster without losing control. At the same time, ways of working become more standardized. The more the system is used, the better it becomes. This is one of the most effective ways to reduce dependency on individual expertise.

One of the most significant changes in recent years is that CAM is no longer a standalone tool. It is part of a larger ecosystem that includes product data management, production control and overall manufacturing process planning. When the same data flows through the entire chain from design to production and back, transparency is created. When this is combined with production data and analytics, it goes beyond visibility. Bottlenecks can be identified, processes optimized and decisions made based on data instead of assumptions. At its best, the system can provide insights that individuals or organizations would not otherwise see.

This is not only relevant for large companies. More and more smaller companies benefit from having a controlled process instead of a collection of separate tools. The machines themselves have not changed in the same way – lathes and milling machines still do what they were originally designed to do. Their value comes from their technical capabilities and control, but development is happening faster in software and digital tools.

Digitalization is no longer a choice, it is a requirement to stay competitive. Regardless of company size, the same rule applies: those who can use data and connect their processes will outperform those who cannot.

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More than a software decision

Choosing a CAM system is no longer just a software decision. It is a decision about how far you want to take your production. Not every solution is for everyone, and it does not need to be. For simpler production, a lighter solution can be enough. But as parts, machines and processes become more demanding, the overall solution becomes more important. That is where the real differences between systems start to show.

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Originally published here.

Manufacturers of complex products are under growing pressure to balance sustainability and profitability. They must reduce carbon emissions and meet rapidly evolving sustainability regulations amidst global, carbon-intensive supply chains that still rely heavily on fossil-based energy and resource-heavy production processes. All while protecting margins.

For complex products with thousands of components, design decisions have asignificant impact on both cost and carbon footprint. Yet, this is exactly where most manufacturing companies lack the necessary insight to act with confidence.

Most critical decisions happen too early and too blindly

Despite significant investments in PLM, CAD, and MOM systems, cost and sustainability insights remain disconnected from day-to-day engineering decisions. In practice, costing is still managed through fragmented Excel models with limited traceability, while sustainability is often handled as a downstream reporting exercise rather than an input that actively shapes design choices.

As a result, teams are forced into costly redesign cycles, decision making is slowed down by manual handovers between engineering,finance, and operations, and critical knowledge remains fragmented. At CLEVR, we see it all the time. Both the disruption of daily operations that all of these create for manufacturers, and the clear shift in the market. 

Customers are increasingly looking for transparency into cost structures and environmental impact, and are gradually moving away from viewing PLM, MOM, and CAD systems as end goals in themselves. There is a growing expectation that digital platforms should actively support real business decisions, and this is exactly what we are now better positioned to deliver.

From systems of record to systems of decision making

In practice, most organizations still operate in a reporting mode. Cost calculations are typically based on estimations of material costs, labor, tooling, and supplier pricing, while sustainability metrics often rely on benchmark or reference data. By the time these figures are compiled, major design decisions are already locked in, forcing manufacturers to either accept lower margins or go back to the design phase and rework the product.

With the addition of ET Advisory, these insights can now be embedded directly into the product lifecycle, and redefine how decisions are made. By connecting cost and carbon data directly to the evolving bill of materials, we align engineering decisions with manufacturing realities and supplier inputs.

At the same time, we extend this with a deeper understanding of how product characteristics, performance, and market dynamics influence pricing and margin potential. This allows organizations not only to understand what a product should cost, but also how it should be positioned in the market. 

More specifically, manufacturing teams can:

• Define and control cost targets from the earliest design stages through design-to-cost and target-costing approaches
• Build accurate bottom-up cost models based on product structures, materials, and manufacturing processes
• Assess profitability across the full product lifecycle through scenario-based analysis of margins and investments
• Strengthen procurement with fact-based supplier negotiations through purchase price analysis and should-costing
• Create transparent and competitive pricing structures that reflect both cost drivers and market dynamics
• Optimize tooling and manufacturing investments with detailed tool costing insights

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Instead of working with static estimates, teams can model product costs and emissions at component and assembly level, simulate different design, material, and manufacturing scenarios, and understand how these decisions impact both cost and market positioning.

A unified digital thread for engineering, cost and sustainability

With the addition of ET Advisory, CLEVR evolves from an implementation partner into atrue decision enabler.

By activating engineering, procurement, and finance insights across the entire product lifecycle, we can help companies operate on the same data, evaluate trade offs early, and make informed decisions, creating a dynamic and actionable view of product cost, footprint, and value. This is particularly critical for industries such as automotive, industrial machinery, heavy equipment, and defense, where product complexity requires full process transparency and confidence to make timely, data-driven decisions.

Building on our expertise in PLM, Low Code, Data Science and AI, we embed specialized costing and sustainability expertise directly into our delivery model, ensuring that these insights are not only available, but actively used within engineering and business processes.

For customers, this unlocks a fundamentally different way of working. They can leverage value-driven use cases such as design optimization, supplier negotiations, new program planning, global sourcing decisions, and tooling benchmarking, as well as pricing-focused ones like initial price discovery, supplier consolidation, and portfolio cleanup to name a few.

CLEVR: Building the connected future of digital engineering

With the addition of ET Advisory, CLEVR is better positioned to help customers across the Benelux, DACH, and the Nordic regions to not only build their digital backbone, but actively use it to drive cost, sustainability, and product outcomes.

In this way, existing Siemens investments evolve from systems of record into decision engines. And CLEVR is driving this shift enabling companies to move from reactive decision-making to designing products that are cost-efficient, compliant, and sustainable by design.

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For OEMs and machine builders, delivering a machine is not the end of the process. It is the beginning of a long operational lifecycle where performance, uptime, and customer experience define real value.

Yet in many organizations, this lifecycle is still fragmented.

While engineering, planning, and production are increasingly connected across PLM, ERP, and shop floor systems, after sales and field operations often remain disconnected. Service teams operate in separate tools, field technicians lack full machine context, and customer interactions are only loosely linked to core business systems.

The result is a gap in visibility exactly where it matters most.

In this article, we explore how machine builders and equipment manufacturers can break this cycle of inefficiency. How they can finally connect after sales to their core operations, unlock true end to end visibility, and establish closed loop systems that continuously feed insights back into the business.

After sales in manufacturing is a core operational layer

After sales should not be treated as a support function on the side. For machine builders, it is a core operational layer, just as critical as PLM, ERP, and production systems. It is where customer satisfaction is shaped in real time, uptime and performance are delivered, long term relationships are built, and recurring revenue opportunities are unlocked.

When after sales and field service management are not connected to core systems, OEMs lose visibility, control, and the ability to act proactively across the machine lifecycle. This disconnect turns service into a reactive function and creates daily operational friction:

• technicians work without full asset and service history context
• service teams rely on manual updates and disconnected field service management software
• communication between OEMs, dealers, and customers becomes fragmented
• data from the field is not fed back into engineering or quality processes

These challenges translate directly into lower first time fix rates, higher operational costs, and inconsistent customer experiences. Over time, this impacts brand perception and makes it increasingly difficult to scale service as a competitive business capability.

To overcome this, manufacturers must move beyond isolated improvements and adopt an approach that connects after sales in manufacturing end to end, aligning field service management processes with core systems and business objectives.

From fragmented field service management tools to connected operations

OEMs today have access to an abundant and mature toolkit of solutions for after sales in manufacturing and field operations, each effectively solve a respective pieces of the service lifecycle puzzle:

• ‍Field service management systems can help plan and dispatch work, optimize technician schedules, and increase first time fix rates by ensuring the right skills are sent to the right job at the right time.
• ‍IoT and remote monitoring platforms can collect machine data, trigger alerts, and provide visibility into equipment performance, enabling earlier detection of issues and condition based maintenance.‍
• ERP and service modules can manage contracts, warranties, installed base, and billing, ensuring financial control, service-based revenue models, and a structured view of customer agreements and obligations.‍
• Customer portals can improve transparency and communication by giving customers access to service status, documentation, and support channels. 

But even when OEMs invest in all these tools, they are still faced with one fundamental problem: disconnection.

What OEMs are missing is not another tool, but a way to connect these capabilities into a self feeding lifecycle. A connected operating model where data, workflows, and insights continuously flow across systems, teams, and the full machine lifecycle.

With low code for manufacturing, OEMs can create that connection layer, enabling customized solutions that evolve with their operations and unlock true lifecycle connectivity and continuous improvement.

Connect manufacturing and field service management operations with low code

Instead of forcing operations into predefined software structures, a low code platform for manufacturing enables OEMs to design and orchestrate after sales and field service management processes around their own workflows, systems, and business priorities.

Positioned on top of PLM, ERP, shop floor, and service systems, low code acts as a connection layer built from reusable building blocks. These blocks extend existing systems and connect them into one unified experience, bringing machine builders and equipment manufacturers closer to a truly orchestrated, self feeding lifecycle.

More specifically, low code enables OEMs to:

1. Connect systems into one workflow

Low code connects existing systems and transforms isolated data into coordinated, end to end workflows. For OEMs, this means embedding intelligence directly into field service management processes, enabling faster decisions, reducing manual effort, and ensuring every action is driven by real time insights.

2. Unlock proactive service

With industry leaders reporting measurable reductions in downtime when moving toward predictive service models, the value becomes tangible. Low code turns machine signals and service data into automated workflows, allowing OEMs to resolve issues before they impact operations, improve customer satisfaction, and unlock new service revenue models.

3. Enable AI driven and future ready service models

Low code provides the flexibility to design workflows that match real operational complexity. OEMs can integrate AI, analytics, and automation into their field service management processes as they evolve, enabling continuous innovation without disrupting existing systems.

4. Scale without replatforming

Low code enables OEMs to start small and expand gradually. New capabilities, systems, and workflows can be added over time, creating a scalable foundation for connected service operations without replacing core platforms.

5. Deliver faster time to value

OEMs can rapidly build and deploy tailored solutions such as service case management, mobile field service management apps with full asset context, proactive maintenance workflows, partner collaboration portals, and customer engagement platforms, often in a matter of weeks.

CLEVR enables connected service operations with a low code accelerator

At CLEVR, we bring this approach to life through a Mendix based accelerator designed specifically for OEMs and machine builders. Rather than starting from scratch, the CLEVR Filed Service Management Solution provides a proven foundation that can be quickly tailored to each organization’s needs:

• ‍A core foundation. A reusable base that includes best practices for after sales and field service management processes.
• ‍Configurable modules. Predefined components that support workflows such as service cases, work orders, inspections, and asset management.‍
• Tailored extensions. Custom capabilities built to match unique processes, integrations, and business models.

With 30+ years of experience in the Siemens Xcelerator portfolio and advanced low code application development, CLEVR bridges strategy and execution by connecting proven industrial platforms with the flexibility required to adapt to evolving operational demands. Over the years, we have partnered with multiple OEMs and machine builders to deliver connected service operations tailored to their specific needs.

By starting with focused, high value use cases and expanding step by step, we help organizations move quickly from fragmented processes to a cohesive, end to end operating model that spans engineering, production, service, and customer interaction.

Our approach is grounded in listening closely to real operational challenges and translating them into practical solutions that work in the field. From unifying service cases, work orders, installed base and asset telemetry into one workflow, to field and partner collaboration, and customer visibility portals our portfolio includes many examples of how we have helped leading manufacturers close the loop across their operational lifecycle.

If you are looking to connect after sales with field service management software and build a truly connected service operation, we know how to help you get ahead.

Contact us for a consultation.