| Annual production volume | Planned good vehicles per year, by model and shift pattern | Strong fit when one platform has stable, sustained demand | Useful when demand is substantial but spread across several models | Useful for staged launches, lower initial volume, or incremental capacity additions | Choose a configuration that meets the forecast without relying on permanent maximum utilization. |
| Required takt time | Available production time ÷ required good units; calculate separately for each constrained process | Designed around a consistent, repeatable cycle | Must accommodate the cycle-time differences between models | Capacity can be added by adding or duplicating work cells | For illustration, 4,000 scheduled hours per year and 50,000 units require an average takt of 288 seconds per unit before allowances for breaks, downtime, and losses. |
| Model and platform mix | Number of body styles, wheelbases, battery configurations, and option combinations | Best when product variation is limited and the product plan is stable | Best when multiple compatible models must share equipment | Best when processes can be separated into independently configured modules | Confirm that all intended variants fit the equipment, fixtures, and material-flow design. |
| Changeover requirements | Changeover time, tooling changes, software settings, and verification steps | May need dedicated tooling or planned model-specific production windows | Requires validated changeover procedures and model identification at each station | Can isolate some changes to a module, depending on process integration | Use measured trials and supplier cycle-time studies; do not assume changeover is instantaneous. |
| Equipment utilization and availability | Overall equipment effectiveness (OEE), downtime, speed loss, and first-pass yield | High utilization can support strong output but makes bottlenecks especially important | Model mix and routing can affect utilization and line balance | Local disruptions may be contained, subject to buffers and routing design | Set site-specific targets and define OEE consistently; OEE is availability × performance × quality. |
| Battery-pack handling and safety | Pack mass and dimensions, lift method, isolation checks, fire detection, and emergency response | Can support dedicated, standardized pack installation and test stations | Needs flexible fixtures and verified procedures for each supported pack variant | Can place pack assembly or testing in a separate controlled module | Require a documented risk assessment, safe lifting design, electrical-safety controls, and applicable local-code compliance. |
| Quality and end-of-line testing | First-pass yield, defect escape rate, torque records, leak tests, and electrical checks | Repeatable stations can simplify process control for a stable product | Requires recipe control and clear variant verification at each relevant station | Testing modules can be expanded or reconfigured as product requirements change | Define required tests, acceptance limits, and rework routes before finalizing the line layout. |
| Traceability and data integration | Vehicle identification, component genealogy, process results, and data-retention needs | Can collect consistent station-level data for a standardized flow | Needs reliable model- and option-specific routing and process parameters | Needs consistent data interfaces across modules and stations | Verify that each critical operation can be linked to the finished vehicle record. |
| Labor and automation strategy | Staffing by shift, ergonomic exposure, automation level, and maintenance skills | Automation may be economical for repetitive, high-volume tasks | Automation must tolerate model variation and changeover needs | Can support selective automation and phased staffing changes | Automate where repeatability, safety, quality, or lifecycle cost justifies it—not simply to maximize robot count. |
| Footprint and material flow | Floor area, aisle access, buffer space, inbound routes, and finished-vehicle flow | Often benefits from a continuous, carefully balanced flow | Needs space for variant-specific parts and flexible logistics routes | Requires room for module access, separation, and possible future additions | Validate the layout with equipment envelopes, maintenance access, safety clearances, and material-flow simulations. |
| Investment and lifecycle cost | Total installed cost, tooling, utilities, training, maintenance, and cost per good vehicle | Investment can be easier to justify at consistently high volume | May reduce the need for separate lines but can require more complex changeover capability | Can support phased investment; integration and duplicated equipment still need evaluation | Compare total cost over the planned product life, including ramp-up, model changes, and downtime. |
| Expansion and product changes | Time, cost, and disruption needed to add shifts, models, stations, or capacity | Expansion may require substantial rebalancing or additional dedicated equipment | Can accommodate compatible models if capacity and routing were designed for them | Well suited to incremental capacity or process changes where interfaces are standardized | Ask for a documented expansion scenario with space, utility, staffing, and shutdown assumptions. |
| Commissioning and ramp-up | Installation schedule, process validation, trial builds, and time to stable good output | Requires coordinated commissioning of a tightly connected flow | Variant validation adds planning and verification work | Modules may be commissioned in stages if interfaces allow independent operation | Include trial production, safety validation, operator training, and corrective-action time in the project plan. |