Mechanical Engineering Design

🛠️Mechanical Engineering Design Unit 14 – Design Optimization & Cost Analysis

Design optimization and cost analysis are crucial aspects of mechanical engineering. These techniques help engineers find the best design solutions while considering performance, constraints, and economic factors. Engineers use various optimization methods, from linear programming to multi-objective approaches, to improve designs. Cost analysis tools, including break-even analysis and lifecycle costing, help balance performance with economic viability. Together, these skills enable engineers to create efficient, cost-effective designs.

Key Concepts in Design Optimization

  • Design optimization involves finding the best design solution that satisfies given constraints and objectives
  • Objectives are the goals or performance metrics to be optimized (weight, strength, efficiency)
  • Constraints are the limitations or restrictions that the design must satisfy (budget, material properties, geometry)
  • Design variables are the parameters that can be changed to optimize the design (dimensions, materials, shapes)
    • Continuous variables have a range of possible values (length, diameter)
    • Discrete variables have a finite set of possible values (number of bolts, material grade)
  • Optimization algorithms systematically search the design space to find the optimal solution
    • Gradient-based methods (steepest descent) use derivatives to guide the search
    • Heuristic methods (genetic algorithms) use rules of thumb to explore the design space
  • Pareto optimality occurs when no objective can be improved without worsening another objective
  • Sensitivity analysis studies how changes in design variables affect the objectives and constraints

Fundamentals of Cost Analysis

  • Cost analysis estimates the total cost of a product or system over its lifecycle
  • Fixed costs remain constant regardless of production volume (rent, equipment)
  • Variable costs change with production volume (materials, labor)
  • Direct costs can be directly attributed to a specific product or activity (raw materials, assembly labor)
  • Indirect costs cannot be directly attributed to a specific product or activity (overhead, administration)
  • Break-even analysis determines the production volume at which revenue equals total costs
  • Learning curve effect reduces the unit cost as production volume increases due to improved efficiency and economies of scale
  • Cost estimation methods include analogous, parametric, and bottom-up approaches
    • Analogous cost estimating uses historical data from similar products
    • Parametric cost estimating uses mathematical models based on product characteristics
    • Bottom-up cost estimating aggregates detailed estimates of individual components

Optimization Techniques and Methods

  • Linear programming optimizes a linear objective function subject to linear constraints
    • Simplex method is a common algorithm for solving linear programming problems
  • Nonlinear programming optimizes a nonlinear objective function subject to nonlinear constraints
    • Sequential quadratic programming (SQP) is a popular method for solving nonlinear problems
  • Integer programming optimizes an objective function where some or all variables are restricted to integer values
  • Multi-objective optimization involves optimizing multiple conflicting objectives simultaneously
    • Weighted sum method combines multiple objectives into a single objective using weights
    • Goal programming minimizes the deviation from target values for each objective
  • Stochastic optimization handles uncertainties in the design variables or parameters
    • Monte Carlo simulation samples random variables to estimate the probability distribution of outputs
  • Topology optimization finds the optimal material distribution within a given design space
    • Solid Isotropic Material with Penalization (SIMP) method is widely used in structural optimization

Economic Factors in Design

  • Time value of money accounts for the fact that money available now is worth more than the same amount in the future due to potential earning capacity
    • Present value (PV) is the current value of a future amount of money
    • Future value (FV) is the value of a current amount of money at a specified date in the future
  • Discount rate is the interest rate used to determine the present value of future cash flows
  • Inflation is the rate at which the general level of prices for goods and services is rising
  • Depreciation is the decrease in value of an asset over time due to wear and tear or obsolescence
    • Straight-line depreciation assumes a constant rate of depreciation over the useful life of the asset
    • Accelerated depreciation (double-declining balance) allows for higher depreciation charges in the early years of an asset's life
  • Taxes impact the cash flows and profitability of a design project
    • Income taxes are levied on the taxable income generated by the project
    • Property taxes are assessed on the value of the project's assets
  • Economic analysis methods include net present value (NPV), internal rate of return (IRR), and payback period
    • NPV is the sum of the present values of all cash inflows and outflows over the project lifecycle
    • IRR is the discount rate that makes the NPV of the project equal to zero
    • Payback period is the time required to recover the initial investment

Trade-offs Between Performance and Cost

  • Performance and cost are often competing objectives in design optimization
    • Improving performance (speed, accuracy) may increase cost (materials, manufacturing)
    • Reducing cost may degrade performance (reliability, durability)
  • Pareto frontier represents the set of optimal solutions that trade off performance and cost
    • Solutions on the Pareto frontier cannot be improved in one objective without worsening the other
    • Knee point is the solution on the Pareto frontier that offers the best balance between performance and cost
  • Cost-benefit analysis quantifies the benefits and costs of different design alternatives
    • Benefit-cost ratio (BCR) is the ratio of the present value of benefits to the present value of costs
    • Alternatives with a BCR greater than 1 are considered economically viable
  • Value engineering systematically analyzes the functions of a product or system to optimize value
    • Value is defined as the ratio of function to cost
    • Techniques include functional analysis, creative brainstorming, and cost reduction strategies
  • Design for X (DFX) methodologies optimize designs for specific objectives such as manufacturing, assembly, or sustainability
    • Design for Manufacturing (DFM) minimizes manufacturing costs and complexity
    • Design for Assembly (DFA) reduces assembly time and errors
    • Design for Sustainability (DFS) considers environmental impacts and resource efficiency

Software Tools for Design Optimization

  • Computer-aided design (CAD) software creates and modifies 2D and 3D models of products
    • Parametric modeling allows easy changes to design variables and constraints
    • Finite element analysis (FEA) simulates the behavior of designs under loads and boundary conditions
  • Optimization software integrates with CAD to automate the search for optimal designs
    • Altair OptiStruct is a popular tool for structural optimization
    • ANSYS DesignXplorer performs parametric studies and design of experiments (DOE)
  • Multidisciplinary design optimization (MDO) tools coordinate the optimization of multiple interacting disciplines (structures, aerodynamics, controls)
    • OpenMDAO is an open-source framework for MDO
    • ModelCenter integrates disparate models and automates trade studies
  • Data analysis and visualization tools help explore the design space and communicate results
    • JMP is a statistical software package for DOE and data analysis
    • Tableau creates interactive dashboards and visualizations
  • High-performance computing (HPC) enables the optimization of computationally expensive models
    • Parallel processing distributes the workload across multiple processors or cores
    • Cloud computing provides on-demand access to HPC resources

Case Studies and Real-World Applications

  • Aerospace industry uses design optimization to minimize weight and maximize performance of aircraft and spacecraft components
    • Boeing optimized the wing design of the 787 Dreamliner for fuel efficiency and structural integrity
    • NASA used topology optimization to design lightweight brackets for the Mars Perseverance Rover
  • Automotive industry applies optimization techniques to improve fuel economy, safety, and comfort of vehicles
    • General Motors optimized the engine design of the Chevrolet Volt for high efficiency and low emissions
    • Tesla used multi-objective optimization to balance the range, acceleration, and cost of the Model S
  • Manufacturing sector optimizes production processes and supply chains to reduce costs and increase productivity
    • GE Aviation used additive manufacturing and topology optimization to create fuel nozzles with improved performance and reduced lead time
    • Siemens employed simulation-based optimization to optimize the factory layout and production scheduling of a gas turbine plant
  • Construction industry optimizes the design and planning of buildings and infrastructure projects
    • Arup used parametric modeling and optimization to design the steel roof structure of the Beijing National Stadium (Bird's Nest)
    • Bechtel applied linear programming to optimize the resource allocation and scheduling of a multi-billion dollar pipeline project
  • Computational complexity of optimization problems increases exponentially with the number of design variables and constraints
    • Curse of dimensionality refers to the challenge of exploring high-dimensional design spaces
    • Surrogate modeling techniques (response surface methodology) can reduce the computational burden by approximating the expensive models
  • Uncertainty and variability in the design parameters and operating conditions can affect the optimality and robustness of the solutions
    • Robust optimization finds solutions that are insensitive to variations in the input parameters
    • Reliability-based design optimization (RBDO) ensures that the design satisfies reliability constraints under uncertainty
  • Integration of artificial intelligence (AI) and machine learning (ML) techniques can enhance the efficiency and effectiveness of design optimization
    • Deep learning can learn complex relationships between design variables and performance metrics from data
    • Reinforcement learning can guide the search for optimal designs through trial and error
  • Collaboration and knowledge sharing among diverse teams and stakeholders is crucial for successful design optimization
    • Concurrent engineering involves the simultaneous design of a product and its related processes
    • Knowledge-based engineering captures and reuses design knowledge to automate routine tasks
  • Sustainability and lifecycle considerations are becoming increasingly important in design optimization
    • Eco-design considers the environmental impacts of a product throughout its lifecycle
    • Circular economy promotes the reuse, recycling, and recovery of materials and products


© 2024 Fiveable Inc. All rights reserved.
AP® and SAT® are trademarks registered by the College Board, which is not affiliated with, and does not endorse this website.

© 2024 Fiveable Inc. All rights reserved.
AP® and SAT® are trademarks registered by the College Board, which is not affiliated with, and does not endorse this website.