Directional & High-Fidelity Cost Models = Accurate Product Cost Estimates

Key Takeaways:

• As cost variances increase, manufacturers get farther away from the true economic cost of a product.
• Digital manufacturing simulation enables more precise insight into the essential production resources that help stabilize a cost foundation influenced by variances.

The Full Article:

Manufacturers continue to face challenges, including higher materials prices, labor shortages, and supply chain issues. There is added pressure to reduce cost drivers and time to market. These challenges, along with supply chain and workflow disruptions, compound the issue with reactionary and siloed decision-making. Far too many manufacturers rely on a manual approach and an insufficient number of engineers to analyze and respond to cost, manufacturability, and/or sustainability requests and data.

Consequently, productivity is bottlenecked. Last-minute, unforeseen design changes lead to excessive and costly engineering change orders and delays. Manufacturability, cost, and sustainability optimization opportunities are lost due to a lack of insights early in product development. Lastly, cost targets and profit margins fall short.

The good news is that directional and high-fidelity cost models can help lower costs and get a more accurate estimate of a product’s true cost.

What Are Directional and High-Fidelity Cost Models?

Directional costing is an accounting methodology. It models industry averages in terms of processes, cycle times, and labor/overhead rates.

Directional costing is helpful (and accurate enough) in making short-term decisions (pricing, a new product line, or profitability), outlier identification, and design for manufacturability (DFM). It analyzes incremental, fluctuating costs such as raw materials. However, directional costing lacks inputs and modeling needed to provide a predictive cost estimate. It cannot be used for self-quoting and meeting cost targets.

Overall, directional costing is an efficient, short-term method of controlling costs and basing decisions on their direct financial impact. Although it does account for both direct and indirect costs, it is an industry average.

A high-fidelity cost model, which factors in both direct and indirect costs, is tailored to a customer’s specific components, supply base, and processes. Additionally, it is a cost estimate in which the inputs have been highly refined to match the latter.  It is a highly accurate predictive cost estimate and more precise in meeting target costs. However, it does require a high degree of knowledge costing inputs or large configuration amounts.

Get Closer to the True Economic Cost

Cost modeling tools are only as good as the solutions or processes behind them. Using a digital twin CAD model to automatically simulate the entire production process can help manufacturers get closer to a product’s true economic cost.

A directional cost model analysis can get you closer to the true economic cost. A high-fidelity method more precisely calculates the true economic cost of a product, component, or assembly. Ascertaining the necessary production resources is essential. aPriori facilitates this process, identifying the issues that can influence the true cost and profit margins.

Product teams can get should cost and early visibility, maximize product development opportunities, boost productivity, and accelerate time to market. The analysis provides context that can drive better decision-making for stakeholder and organizational needs.

A shared single source of truth enhances organizational transparency and collaboration. Equally important, a consistent digital trail optimizes product development at every stage.

aPriori Supports Directional and High-Fidelity Cost Models

PLM systems can be used for much more than a repository for 3D CAD files and manufacturing information. They can contain cost, manufacturability, and sustainability analysis history via design iterations. This means that data for directional reporting is stored directly in the PLM. As a result, this data builds over time and helps to narrow in on critical insights and recommendations that improve design, cost, sustainability, sourcing, and production.

Integrating a PLM ensures that product development teams have the right access and ability to see the 3D models. More importantly, they get real-time manufacturability, cost, and production feedback while still in the design stage. As a result, time to market is not impeded and teams can ensure that cost targets are met. It also provides specific feedback and criteria. Workloads can be prioritized, stakeholders notified of potential risks, and a link to resolve the issue in aP Design and/or aP Workspace can be provided. The latter also validates assumptions and collects and stores data for decision-making.

Product development teams can focus on the insights most relevant to their roles, receiving directional feedback rather than just should cost data. For instance, aPriori’s aP Generate integrates with your PLM system. Users like procurement can scale the analysis of parts once the trigger (an event or condition that initiates an action or process) is met in the PLM system, boosting speed and scalability. It then generates high-fidelity results that foster strategic decision-making (with key insights tailored to relevant stakeholders’ roles) and further evolves the design. For example, cost engineers want to identify parts at risk of exceeding target amounts, whereas design engineers are focused on reducing manufacturability risks in their designs.

However, this fidelity depends on the maturity level of the customer’s PLM and whether they add the attributes into the PLM, from which they then could pull. For example, a design engineer pushing through their first design concept likely will not know the correct inputs. In this case, the PLM would provide a more directional result. As the design evolves and is validated with other teams, aPriori fine-tunes the result. It then becomes more precise. If users default the inputs when setting up the aP Generate workflow, then the result will be more directional in nature.

Unlike other cost analysis and system of record tools, aPriori alerts users to items at risk for product delays due to high costs, manufacturability issues, or a high CO₂e footprint. Manufacturers can assess cost reduction opportunities, analyze trade-offs, and mitigate manufacturability risk earlier in product development.

By leveraging aPriori and directional and high-fidelity cost models, product development teams can narrow the gap between should cost and actual purchase price, achieving a true economic cost for their products. As a result, they gain the benefits of cost modeling with greater profitability, faster time to market, greater productivity, and cost, manufacturability, and sustainability optimization.