The right modularization method is the one whose module drivers lead to the economic effects you want. A 2022 paper in the ASME Journal of Mechanical Design compares seven methods and links three most clearly to economic targets: Life Phase Modularization, Modular Function Deployment (MFD®) and Strategic & Functional DSM-based Modularization. They work best combined. When I talk with engineering and product managers in Japan, one question comes up again and again: which modularization method should we use? It's a fair question. There are many methods, each with its own vocabulary, and most of them promise lower cost and shorter lead times.
In my experience, though, companies rarely struggle because they picked the "wrong" method. They struggle because they started with the method instead of with the economic result they wanted to achieve.
That’s why a 2022 paper by Schwede and colleagues in the ASME Journal of Mechanical Design caught my attention. Instead of ranking methods, it looks at which reason for forming a module leads to which economic effect. In this article I summarize what the paper found and look closer at the three methods it links most clearly to economic targets. I then add my own view on how to choose and combine them, using three kinds of electric motors as examples.
Modularization is a management and design process. You start from the economic effects you want and translate them into product architecture. This article draws on the paper "How to Use the Levers of Modularity Properly—Linking Modularization to Economic Targets" (ASME Journal of Mechanical Design, 2022), which compares seven representative modularization methods.
To make the methods comparable, the authors look at the one step in each method where module boundaries are decided, which they call the module-forming step (Core Step C). They compare inputs, decision criteria, module drivers, working aids and the life phases each method targets. They then assess whether the reasons for forming modules can be causally linked to cost, time, flexibility and quality, and how many life phases the effects reach. Three methods stand out as having a particularly clear link to economic targets:
Each one starts from a different place. M1 starts from the entire life cycle, M2 from customer value and business strategy, and M3 from strategic intent combined with technical coupling. In practice they work best in combination, chosen to fit the industry, the product structure and the economic targets.
At Modular Management we use MFD as our core method. We use PALMA® to manage modules, variants, interfaces, configuration rules and the reasoning behind each decision over time, so the results become a lasting asset for the company and not just a project report.
Most comparisons of modularization methods look at names or procedures. This paper isolates the step in each method where module boundaries are actually decided, Core Step C, and analyzes all seven methods against the same yardstick.
The authors had a practical reason for this. The benefits of modularization are well known, but practitioners had no comparable information to help them pick the method that fits the economic targets their own company is pursuing. Keeping the external variety the market demands while limiting internal variety in parts, specifications and processes is central to managing complexity costs. Yet the literature described each method in its own format, and the effects of modularization on each life phase and economic target were often left implicit. It was also unclear which economic targets a given set of module drivers affects, and through which pathways.
So the authors didn't rank the methods. They extracted the reasons each method uses to form modules and linked those reasons to economic effects. The aim is to let designers, engineers and product planners choose a method by working backward from the economic targets they want to reach, and not by name or popularity. The authors call module drivers the "levers of modularity", and their comparison shows which lever leads to which effect.
Figure 1 shows how they did it. Each method's module-forming step is described in the same format, which makes the different decision criteria and links to economic effects comparable.
Figure 1. Generic method-step description of the module-forming step (original)
The comparison uses five criteria:
To link drivers to economic effects, the paper uses the Impact Model of Modular Product Families. The model traces how modular product design affects cost, time, flexibility and quality across the life phases. An "access point" is where a design decision enters that model. It isn't an economic indicator in itself but the start of a chain of cause and effect that runs roughly like this:
So instead of the simple explanation "we group parts because we want lower cost", the model traces which design decision, through which intermediate changes, ends up producing an economic effect.
Three module drivers show how this works in practice:
The key insight is that two projects can both be called modularization and still produce very different effects, depending on the drivers used. Grouping technically coupled elements may bring economic benefits, but only as a by-product. Setting boundaries for reasons such as separate testing, sourcing, service or upgrading lets you say in advance what will improve, and in which life phase.
One caveat: the model doesn't calculate monetary effects. It makes the causal pathways explicit, so that method choices and effect hypotheses can be compared.
Figure 2. Generic method-step description of the module-forming step (detailed)
The paper compares seven methods:
M4 to M7 are effective for specific issues, such as technical integration, differences in component lifetimes, variety and productivity. But on two dimensions M1 to M3 come out ahead: how deliberately module boundaries can be designed for economic effects, and how many life phases those effects reach. In Figure 3 that places them in the upper right.
Figure 3. How strongly seven representative modularization methods focus on economic effects
Note: A conceptual diagram based on the paper’s comparative analysis, not a quantitative assessment.
M1 covers the whole life cycle and has the most access points to economic effects. M2 builds business objectives directly into module formation through module drivers. M3 adds an assessment of technical coupling to M2's strategic focus, which makes the result easier to implement. M4 to M7, by contrast, focus on specific technical rationales or processes.
The rest of this article focuses on M1, M2 and M3. For each one I cover the basic idea, where it comes from, where it has been applied and what kind of product it suits.
M1 sets module drivers for each life phase (development, sourcing, production, sales, service and disposal), creates a preferred module concept for each phase and then integrates them into one. It suits products where the units that make sense in development differ from those that make sense in production, installation and maintenance. Its strength is that it lets you design deliberately for life-cycle cost, including long-term maintenance, replacement, upgrades and recycling.
Origins. M1 was developed around 2010 by a research group at the Institute of Product Development and Mechanical Engineering Design (PKT) at Hamburg University of Technology (TU Hamburg), including Christoph Blees, Henry Jonas and Dieter Krause. It has since become one of the core methods of the Integrated PKT Approach, where it is combined with Design for Variety.
Applications. Early published research applied M1 to an ultra-low-volume (ULV) herbicide sprayer from Mantis ULV-Sprühgeräte GmbH, integrating module concepts from different life phases. Industrial evaluations of the Integrated PKT Approach have also tested it in several company projects, including a gas inlet valve. Many published cases don't name the company, so a full list of users isn't possible. Most applications are at manufacturers of long-life industrial equipment, plant equipment and product families.
MFD makes explicit why elements belong together and why they should be kept apart. It does this through module drivers such as Carry-over, Separate Testing, Supplier, Service and Upgrading, and groups technical solutions into modules accordingly. Because it starts from customer value and business strategy, it lets you decide deliberately where to share and where to differentiate. That makes it effective for high-variety products and product families. At Modular Management, MFD is our core method, and we manage the decision rationale, modules, variants, interfaces and configuration rules in PALMA.
Origins. Gunnar Erixon developed MFD as part of his doctoral research at KTH Royal Institute of Technology in Sweden. It became widely known through the book Controlling Design Variants: Modular Product Platforms (1999) by Anna Ericsson and Gunnar Erixon. Modular Management has since developed MFD into a practical method that connects customer value, business strategy, technical solutions, module drivers, interfaces and configuration rules.
Applications. Erixon's early research applied the method to several industrial cases, including mobile winches, car doors and fronts, fifth wheels and drawbar couplings for heavy trucks, servo drives and vacuum cleaners. Modular Management's published cases include Whirlpool, ESAB and MTS, which have used MFD to build product architectures, commonality, configuration rules and configure-to-order capabilities. MFD is widely used by companies with high-variety products and product families, in automotive and transportation equipment, industrial equipment, home appliances and medical devices.
M3 combines a strategic DSM, derived from MFD, with a functional DSM that maps technical couplings such as material, energy and information flows. For elements you'd like to separate or share for strategic reasons, it checks whether they can actually be decoupled technically. The result is a module structure that can be built without losing the economic effects. It works well where technical coupling is strong, as in mechatronics and other complex assembled products.
Origins. Michael Blackenfelt proposed and developed M3 in 2000 and 2001 at KTH Royal Institute of Technology in Sweden. He combined two matrices: MFD's Module Indication Matrix (MIM), which captures the strategic side, and the Design Structure Matrix (DSM), which captures functional and technical dependencies. Together they let you assess, at the same time, which boundaries are desirable for the business and which are technically feasible.
Applications. The original work uses the modularization of a vacuum cleaner to show how the strategic and functional DSMs are combined. Blackenfelt and colleagues also studied modularity practice at five Swedish companies, looking at how product structure, organizational change, technology change, software and electronics affect module boundaries. As with M1, many published cases don't name the company, so there are fewer named public cases than for MFD. Research and practical work combining DSM and MFD has continued since, mainly for products with many parts and strong mechanical, electrical and control dependencies, such as in the automotive industry.
Table 1: The three methods at a glance
|
Method |
Starting point |
Strength |
Main economic effects |
|
M1 |
Entire life cycle |
Long-term, holistic optimization |
Maintenance and replacement time, life-cycle cost |
|
M2 (MFD) |
Customer value and business strategy |
Clear causal link between reasons and results |
Commonality, development lead time, fewer unique parts, sourcing and production efficiency |
|
M3 |
Strategic intent and technical coupling |
Balances strategy with technical feasibility |
Change impact, development risk, test and verification efficiency |
In this section I give my own view on which methods tend to fit which situations. Please treat it as a starting point, not a fixed rule. In my experience, the right method depends less on the industry than on the company's position in it. An original equipment manufacturer (OEM), a system integrator, a component supplier, a contract manufacturer and a service provider can make the same product and still differ in customer contact, exposure to changing requirements, scope of performance guarantees, revenue sources, inventory responsibility and responsibility for maintenance and upgrades. Each of those differences changes which economic effects matter most, and so which module boundaries make sense.
The choice also changes over time. When market requirements, technology, supply chains, make-or-buy decisions, sales models, service models or life-cycle responsibilities shift, the methods a company should lean on shift with them. In automotive, for example, M2 is effective when a vehicle OEM designs commonality and differentiation across a product family. M3 becomes important when verifying subsystem boundaries with strong mechanical, electrical and software coupling. And in businesses responsible for spare parts, upgrades and recycling, M1 carries more weight.
So before using the overview below, look at the company's value proposition, product responsibility, supply model, service scope and target economic effects. Then select and combine M1 to M3, and revisit the choice as circumstances change.
Typical examples: industrial machinery, heavy industry, plant equipment and custom equipment.
Requirements differ for each project, design changes are frequent, and installation, retrofits and maintenance continue for many years. Because the preferred modules differ from one life phase to the next, I'd make M1 the primary method and use M3 alongside it for areas with strong technical coupling.
Typical examples: industrial equipment, commercial equipment, medical devices and other B2B products.
Variants, parts, drawings, tests and suppliers tend to multiply, yet the differentiation customers value has to be kept. MFD makes the reasons for commonality and differentiation explicit, so you can reduce internal complexity while keeping the variety customers care about. Where service makes up a large share of the business, M1 is a useful complement.
Typical examples: machine tools, cars and car parts, electrical equipment and robots.
Mechanical, electrical and software coupling is strong, so standardization goals alone can't set the boundaries. M3 combines strategic and functional DSMs to balance commonality, sourcing and serviceability against technical constraints such as heat, vibration, information and energy.
Typical examples: chemicals, food, materials and energy.
Material transformation processes and equipment are tightly integrated, which leaves little room to split up the product as a whole. Here I'd narrow the scope to maintenance, auxiliary equipment, ancillary facilities and replacement units. M1 defines the upgrade and maintenance units, and M3 verifies coupling related to fluids, heat, pressure and materials.
Typical examples: home appliances, cars and consumer products.
The challenge is to balance market-specific variety with productivity, cost and stable quality. MFD separates the differences customers can see from the shared internal structure. Where needed, it can be combined with the perspective of M7 (Product Family Architecture for Mass Customization) on manufacturing cost, volume and process constraints.
To make this concrete, here are three kinds of electric motor. They're all motors, but the business model, customer contact, product responsibility and supply model differ, and so does the method that fits best. The three are an engineer-to-order motor, a catalog stock motor and a dedicated motor for an in-house pump system (Figure 4).
Figure 4: Three types of motors
This motor is built to customer requirements, with its own design, bill of materials and manufacturing drawings for each project. Requirements cover torque, duty cycle, safety, installation environment, mounting, power supply, maintenance and inspection, and service continues long after delivery.
I'd work in three steps. First, use M1 to sort the requirements for development, production, installation and service. Next, use MFD with drivers such as Carry-over, Separate Testing and Service to decide what can be reused. Finally, use M3 to verify the couplings that can't be broken, such as mounting, vibration, heat, cooling and bearings.
Likely modules are the electromagnetic core, shaft and bearings, cooling, brake, housing, seals, terminal box and sensors. Each interface is defined as a standard specification plus variable parameters, so design changes stay limited to parameters such as flange diameter, shaft diameter, voltage and cooling capacity.
This motor has standard couplings and wiring connectors, performance specifications published in a catalog, and some finished-goods inventory. The main challenge is to cover the market and deliver quickly without adding more stock keeping units (SKUs).
MFD is the primary method here. It separates the variants customers value (output, speed, mounting, protection class and connections) from the elements that should be shared, such as the electromagnetic core, bearings, enclosure and terminal system. Because manufacturing cost, volume and inventory turnover matter a lot, M7's perspective is a useful complement. Managing standard interfaces and configuration rules in PALMA keeps sales and manufacturing configurations aligned, prevents configuration errors and helps optimize inventory and supply lead times.
This motor is made in-house as part of a hydraulic pump system. It has to meet special environmental and geometric requirements, and its performance is guaranteed at system level. Here, the technical coupling with the pump, controls, cooling and housing matters more than standardizing the motor on its own.
M3 is therefore the primary method, with DSMs used to map dependencies in torque transmission, vibration, heat, fluids, control and mounting. MFD's strategic drivers are used in parallel to decide which elements should be shared across the pump system, which should be made in-house, which should be tested on their own and what the service replacement units are. M1 complements this when looking at replacement units for maintenance and upgrades, and at differences in system lifetimes.
Table 2: Method choice for the three motors
|
Motor type |
Main challenges |
Primary method |
Supporting methods |
|
Engineer-to-order |
Project-specific requirements and long-term service |
M1 |
M2, M3 |
|
Catalog stock |
Market coverage, SKUs, inventory, short delivery times |
M2 (MFD) |
M7 |
|
Dedicated to pump system |
System coupling and overall performance guarantee |
M3 |
M2, M1 |
The paper's main message is to start by deciding which economic effects you want, in which life phases and over what time horizon. Then you select and combine methods to fit your product structure and business model.
In that flow, M1 sets the scope of effects across the whole life cycle, M2 turns customer value and business strategy into a module structure through module drivers, and M3 makes that structure technically feasible. MFD sits at the center, connecting commonality and differentiation, reuse and change, and strategy and design. With PALMA, the decision rationale, variants, interfaces and configuration rules stay available and up to date across functions. I believe that's what turns modularization from a one-off project into a lasting business capability.
Related information: The MFD® methodology / Modular Management solutions and customer cases / PALMA® features and benefits
"How to Use the Levers of Modularity Properly—Linking Modularization to Economic Targets" is a peer-reviewed paper, published online on March 24, 2022, and in the July 2022 issue of the ASME Journal of Mechanical Design. Its main contribution is to treat each method's module drivers as levers of modularity and connect them, through access points, to the Impact Model of Modular Product Families. This article builds on that framework and adds my own view on applying M1, M2 and M3 by industry and situation, illustrated with three types of motors.
Original paper: How to Use the Levers of Modularity Properly, ASME Digital Collection