Multiple manufacturing technologies in a single assembly
Generic costing methods treat complex assemblies as if they were a single, flat line item. They ignore that cost is created through multiple overlapping manufacturing processes, each with its own setup time, tooling logic, and routing.
For example, a hydraulic powerpack involves fabricated tanks, welded frames, machined manifolds, pumps, valves, wiring, and coating. BOM rollups and simple multipliers can’t capture the layered process cost behind this kind of build.
Low to medium volumes with high variability
Many industrial equipment programs are built in small quantities or for specific customer requirements. In these cases, setup time, fixture changeovers, and the way operators work have a much bigger impact on cost than in mass production. But traditional costing methods are based on mass production assumptions - stable routing, low setup per part, and predictable cycles. That’s simply not the reality for this kind of equipment.
For example, when a CNC machine base frame is made in small batches, there are frequent setup changes, operator differences, and unpredictable cycle times. Generic costing ignores these variations and gives a number that looks smooth on paper but doesn’t reflect the actual cost.
Region and supplier dependency
A single “global” costing factor doesn’t work in real manufacturing. Costs change a lot depending on where the part is actually made. Things like machine-hour rates, labour costs, logistics, duties, and how the local supplier base works can completely change the final cost.
For example, if you cost the same industrial gearbox in India, Germany, and the U.S., the number will not be the same. Generic costing methods usually just apply a simple multiplier and ignore these differences - and the real gap shows up only during negotiations.
Welds, coatings, and testing are underestimated
Welding, coating, and testing are often treated as afterthoughts, even though they’re some of the most labour- and time-intensive steps in heavy equipment. Most costing methods reduce them to just another line item, which creates a big gap between the estimated cost and the real cost.
For example, a mining excavator bucket involves long weld lengths, surface prep, blasting, painting, and structural testing. Generic costing usually rolls all of this into a single “assembly” cost, which hides the actual effort and underestimates the total cost.
Integration between fabricated and bought-out parts
In most should costing exercises, fabricated and bought-out parts are treated separately, but the cost of putting them together is often ignored. Mounting, alignment, wiring, plumbing, and commissioning all add time and labour that generic costing methods don’t account for.
For example, a motorized conveyor system uses fabricated frames, rollers, gearboxes, motors, sensors, and controls. The cost of integrating these parts is real and significant, but most costing methods leave it out entirely.
Inconsistent input quality and fragmented data
Costing for industrial equipment often starts with incomplete or messy inputs. Teams may have old PDFs, partial drawings, rough BOMs, or teardown notes. Generic costing methods struggle with this kind of data and usually depend on assumptions and averages to fill the gaps.
For example, a heavy press retrofit project might begin with decades-old drawings and missing details. Without a structured way to handle these inputs, teams end up building costs on shaky ground.
Teams working in silos
In many companies, costing lives in separate spreadsheets: Design/Engineering builds one, Cost Engineering another, Procurement/Sourcing and Supplier Negotiation have their own, and so do VA/VE, Finance/Controlling, and sometimes Operations/Manufacturing Engineering. None of these files share the same assumptions on machine rates, scrap, duties, region, or even currency - so the numbers drift.
The result is predictable: everyone shows up to reviews with different versions of the truth, alignment takes weeks, and negotiations stall. There’s no shared platform, no audit trail, and no external validation of inputs. When decisions finally get made, they’re often based on whichever spreadsheet shouted loudest - not on a consistent, defensible should cost.
Detailed BOM and Part-Level Parameter Mapping
xcPEP enables detailed mapping of bill of materials (BOM) and part-level attributes using teardown studies & engineering drawings. For each part, more than 50 parameters are captured, including weight, geometry, box size, wall thickness, coating type, manufacturing category, material grade, surface area, and perimeter.
For mechanical components, data such as mounting methods, joining techniques, casting types, and machining details are also captured. For electrical components, the BOM includes semiconductor details, PCB attributes, number of layers, component placement, and manufacturer references. When drawings are available, parameters are extracted manually or via assisted parsing, enabling xcPEP to generate cost models directly from the data.
The BOM template is process-specific and fully editable. Users can modify it to add new parameters or build entirely new BOM templates as required. All mapped data is structured, traceable, and ready for use within the cost model engine.
Configurable Cost Models
xcPEP allows users to work with structured, editable cost models instead of static templates. Each cost model is built using equations and logic relevant to the specific manufacturing process being costed. Inputs such as material usage, cycle time, tool life, labour effort, and overhead allocation can be adjusted to match internal standards or supplier conditions.
Cost models in xcPEP are fully editable; users can modify them based on actual production flows. New Models can also be created from scratch for new processes, ensuring that cost logic remains relevant as products and technologies evolve. For specific requirements, additional parameters can be mapped into a model. For example, injection moulding models can be extended with user-defined fields beyond the defaults, allowing for deeper process-specific detail when needed.
Build-Your-Own Cost Models
For cases where standard cost models do not apply, xcPEP provides the ability to create fully custom models. Users can define process steps, assign formulas, and build part-specific costing structures from the ground up. Each model follows a consistent framework, allowing for integration with other platform modules. This flexibility ensures that niche processes, proprietary methods, or new product lines can be costed with the same level of control and consistency as standard components.
Input data required for these models, such as material prices, machine rates, or tooling norms, can be fetched from the xcPROC cost data service.
Built-in Cost Dashboards
xcPEP has in built dashboards that display cost breakdowns by part, process, material, supplier, and other filters. Users can view cost distribution as percentages or absolute values, enabling clear understanding of major cost drivers. No third-party BI tools are required; dashboards are built into the platform and update in real time as inputs or assumptions change. All data can be downloaded as Excel files for further analysis or sharing.
Scenario Simulation and Comparison
Users can create multiple scenarios for the same part or assembly by modifying key inputs such as production volume, material grade, process route, or supplier location. Each scenario is stored independently and can be compared using built-in tools. Graphical views allow users to see cost deltas and pinpoint which assumptions contributed to variation. This helps teams evaluate trade-offs before making sourcing or design decisions.
Cost Delta and Driver Analysis
When multiple scenarios or models are available, xcPEP highlights the changes in cost and identifies the key drivers. This helps teams understand how specific assumptions—like cycle time changes or material substitutions—impact final cost. The analysis is integrated into the comparison workflow, making it easy to trace outcomes back to decisions. It supports more informed discussions across engineering, sourcing, and finance.
xcPROC Cost Data Integration
xcPEP connects directly to xcPROC, ASI’s internal cost database. This allows users to access consistent values for raw material prices, machine-hour rates, labour costs, tooling norms, and more. All datasets are built and maintained by ASI and updated on a defined schedule. If a user needs data specific to a plant, region, or process, ASI can build and deliver that subset on request.
Users only subscribe to the datasets they need, and all data is formatted for direct use in xcPEP models. Since xcPROC is natively integrated with xcPEP, users do not need to depend on any third-party applications or external databases for costing inputs.
In Built Idea Tracker
xcPEP includes a dedicated module to capture cost-saving ideas generated during should-costing. Each entry records the proposal details, expected savings, source of the idea, and current status. Teams can use this feature to track progress, assign ownership, and quantify the impact of cost-reduction efforts. The module ensures that valuable insights from costing exercises are not lost and are tied to implementation.
Role-Based Access Control
xcPEP offers granular access control, allowing administrators to define who can view, create, or edit models and data. Permissions can be set at the module, part, or user level. This ensures that teams across engineering, sourcing, and finance have access only to the tools and data relevant to their work. The system supports parallel collaboration without compromising data integrity or control.
Multi-Team Collaboration
Multiple users from different functions can work on the same part or model simultaneously. Engineering teams can define the technical inputs, sourcing can simulate supply-side changes, and finance can view cost outputs—all within the same platform. Access is filtered by role, and activity is coordinated without overlap. This reduces delays and promotes transparency across functions.
Import Tools
xcPEP supports importing BOMs, technical specifications, and costing data from Excel, CSV, and XML formats. Part attributes and cost-related parameters can be bulk uploaded or mapped directly to model fields. This accelerates onboarding of new parts and supports integration with existing workflows. Import formats follow a consistent structure to maintain model integrity.
Custom Reporting and Downloadable Output
All outputs in xcPEP—including full cost breakdowns, comparison reports, and part summaries—can be downloaded in structured Excel formats. Reports are formatted for clarity and ready to be used in internal reviews, supplier discussions, or audits. This enables seamless communication between teams and across functions, while keeping a clear record of cost decisions.
API-Based Integration
The platform provides APIs for integration with external systems such as PLM, ERP, or reporting tools. Data can be exchanged bi-directionally, allowing updates to BOMs, supplier lists, or cost outputs to flow seamlessly between systems. Integration helps avoid duplication of effort and improves alignment with broader digital infrastructure.
AI-Based PCB Component Identification
ASI Engineering uses AI-driven imaging to automatically detect and classify child components on PCBs such as ICs, resistors, capacitors, connectors, and other discrete parts commonly found in PLCs, sensor modules, and actuator controllers. This data is mapped to xcPROC and automatically populates the electronic BOM inside xcPEP, reducing manual work and improving costing accuracy for control electronics.
Bounding Box Dimension Capture System
For mechanical and structural parts like welded frames, castings, hydraulic manifolds, or panel enclosures, laser scanning is used to capture accurate length, width, and height in seconds. This geometric data is directly pushed into xcPEP to calculate blank size, material volume, packaging density, and logistics parameters, grounding cost models in real dimensions.
Automated Projected Area Capture System
For stamped, fabricated, or coated parts such as covers, housings, or mounting plates, xcPEP’s imaging system extracts the true projected surface area. This data is used to calculate finishing, painting, plating, or treatment costs, eliminating dependency on manual drawings and improving BOM consistency.
Internal Cost Lab Setup
xcPEP was deployed to set up an internal cost lab for a global industrial equipment manufacturer with product lines spanning pumps, compressor systems, automation modules, and control cabinets.
The ASI Engineering team managed the entire setup - migrating legacy costing data, configuring part templates, and integrating region-specific input rates using the xcPROC database. This included process routing logic for welded frames, machined housings, hydraulic manifolds, PCB assemblies, and sensor-actuator modules.
ASI worked alongside the client’s engineering and sourcing teams during the initial phase to execute the first few costing projects, demonstrating how to structure process-realistic cost models and simulate sourcing alternatives. The engagement followed a Build–Operate–Transfer (BOT) model. Once the lab was stabilized, full control was handed over to the client. Today, their team runs the lab independently, with ASI providing regular data updates and technical support as needed.
Should-Costing for New Part Development
A leading automation solutions company engaged ASI Engineering to define cost targets for a new robotic control skid during its early concept phase.
The ASI Engineering team built structured cost models directly from CAD and preliminary BOMs - well before supplier sourcing had begun. The models covered key subassemblies, including the welded base frame, machined housing for the hydraulic unit, PCB control module, sensor-actuator blocks, and electrical panels.
Using xcPEP, inputs were configured with validated data from xcPROC - including material grades, machine-hour rates, welding and machining logic, SMT process assumptions, and logistics factors across sourcing regions. As the design evolved, the models were continuously updated to reflect geometry and process changes.
This approach enabled the client’s engineering and procurement teams to align early on realistic cost targets, make design trade-offs based on cost impact, and enter sourcing discussions with a clear internal reference — avoiding late-stage surprises.
Fact Packs for Supplier Negotiations
A manufacturer of industrial process equipment engaged ASI Engineering to support negotiations for a new line of actuator assemblies and control cabinets.
ASI built detailed part-level cost models covering welded structures, machined components, PCB control boards, harness assemblies, and power supply units. Each model reflected actual manufacturing steps such as weld sequencing, machining setup, surface treatment, coating, SMT placement, and final testing - all configured with real-world input rates from xcPROC.
The outputs were compiled into fact packs showing expected cost breakdowns, key assumptions, and cost drivers. These structured packs gave the sourcing team a clear baseline to challenge inflated conversion costs, negotiate confidently, and drive targeted cost reduction actions.
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ASI vs. Management Consultants vs. Benchmarking Companies
Approaches to Cost Optimization for Consumer Electronics Manufacturers
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| ASI – Engineering-Led Cost Transformation | Management Consultants | Benchmarking Companies |
|---|---|---|
| Engineering-led cost transformation using xcPEP & xcPROC, tailored for Consumer Electronics makers. Focus on sustainable, structural cost reduction across full product lifecycles. | Strategy-focused consulting aimed at solving isolated problems. Engagements are billable-hour driven and often lead to recurring cost challenges. | No pre-existing Consumer Electronics database. Deliverables based on expensive, one-off teardown or reverse-engineering projects. |
| Transparent Should Costing for every part, adapted to each manufacturer’s supply base and production process. Highly detailed, data-driven simulations enabling targeted cost-reduction initiatives. | Relies on SME expertise and generic industry data. Often produces incremental changes without addressing systemic cost drivers. | Costing often based on simplistic formulae from limited teardown samples. Insights rarely capture the complexity of electronics manufacturing and electronics child part sourcing. |
Proprietary platforms:
| General financial models and operational frameworks. Lacks manufacturing-specific cost simulation capabilities. | Uses ad-hoc analysis tools for each engagement. No scalable platform for repeatable, accurate cost estimation. |
| Measurable, sustainable cost reductions with direct impact on margin and competitiveness. | Recommendations improve current state but may not deliver optimal or lasting results. | Outcomes are slow, costly, and often fail to justify the investment. |
| Rapid portfolio-wide analysis with live costing tools – weeks, not months. | Multi-month projects from start to final report. | Slow, custom project timelines with long lead times for any usable insights. |
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Engineering Led Cost Transformation
Of Consumer Electronics Manufacturers
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| Challenge | ASI Solution | Value |
|---|---|---|
Key Challenges
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Our Framework
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Business Impact
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| Core Technology Platforms | ||
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xcPROC Procurement Intelligence
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xcPEP Costing Engine Precise Should Costing
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xcPEP Idea Module Automated Design & Commercial Idea Generation
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| Build - Operate - Transfer Engagement Model | ||
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Phase 1: Build Detailed Should-Costing Foundation
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Phase 2: Operate Idea Generation & Implementation
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Phase 3: Transfer Cost Engineering Function Handover
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| Deliverables & Outcomes | ||
Immediate
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Medium-Term
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Long-Term
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