Assessing Lifecycle Value Using Object-Based Modeling by Incorporating Excess and Changeability

Prior research suggests that excess (purposeful inclusion of margin beyond what is required for known system uncertainties) can limit change propagation and reduce system modifications. Reducing change costs increases system flexibility, permitting adaptions that satisfy uncertain future requirements. The benefits of excess, however, must be traded against higher costs of the initial system and likely performance decreases. Assessing the benefits and costs of excess requires evaluating what forms, locations, and magnitudes of excess inclusion are optimal. This paper improves the state-of-the-art in two ways. First, prior research has generally assessed excess in system-level properties (aggregating component properties into a single metric). The approach presented in this paper extends excess assessment to the component level so that the effects of excess on change propagation may be explicitly captured. Second, this approach holistically assesses the value of excess by evaluating both its costs and benefits. The approach borrows from Decision-Based Design and Model Based System Engineering (MBSE) in creating a generic modeling method capable of excess valuation. A desktop computer example is used for demonstrating how excess is valued in a system and the potential gains associated with excess inclusion when mining cryptocurrency. A single component optimization of the power supply capacity for the desktop is assessed to be 750 W, which balances the initial cost against the future flexibility. A system-level optimization then demonstrates the identification of critical change propagation pathways and illuminates both where and how excess may be included to inhibit change propagation. This key component was identified as the motherboard-central processing unit (CPU) slot in the tested systems.

Decision-Based Design Method for Computing Marginal Cost of Durability

Product durability impacts both the environment and the economy. Companies are changing their business models to the circular economy. In this model, the ownership of the product remains with the manufacturer. With this new paradigm, determining the life of the product becomes even more important for the success of the business model. The metric defined as the Marginal Cost of Durability (MCD) determines the cost to increase or decrease the life of the system. For a system to last longer, more materials are needed to counteract the fatigue damage. While this metric has been defined and used in studies throughout the literature, there is a need for a formal method of collecting this data. This paper presents a novel method for measuring the MCD aided by Metamodel-Based Optimization. A case study is presented to demonstrate this method when applied to a wind turbine tower. The results indicate that there is an increasing linear relationship between life and cost. A wind turbine tower designed for 80 years has 34% more mass and cost than a 20-year design.

Multi-Objective Design Exploration of a Canine Ventriculoperitoneal Shunt for Hydrocephalus

Hydrocephalus is a condition that affects humans and animals in which excess cerebrospinal fluid (CSF) builds up within the ventricles of the brain, causing an increase in intracranial pressure. The CSF can be released using a ventriculoperitoneal shunt, which effectively removes the fluid from the ventricles of the brain to the peritoneal cavity. In canines, hydrocephalus is sometimes a fatal condition complicated by shunt failure due to obstructions. The medical procedure is also expensive and has a high failure rate over the long term. In this paper, we present a systematic framework to carry out the multi-objective design exploration of canine shunts for managing hydrocephalus. We demonstrate the efficacy of the framework by designing a shunt prototype to meet specific goals of meeting the CSF flow rate target, minimizing shear stress on the shunt, and minimizing shunt weight. The shunt design variables considered for the problem include the inner diameter, inlet hole diameter, and the distance from the inlet holes to the outlet. A multi-objective design problem is formulated using the systematic framework to explore the combination of shunt design variables that best satisfy the conflicting goals defined. The framework and associated design constructs are generic and support the formulation and decision-based design of similar biomedical devices for different health conditions.

Inverse Thermo-Mechanical Processing (ITMP) Design of a Steel Rod During Hot Rolling Process

The production of steel products involves a series of manufacturing processes. The material Thermo-Mechanical Processing (TMP) history at each process affects the final properties and performances of the product. Experiments and plant trials to predict these properties and performance of steel products are expensive and time consuming. This has resulted in the need for computational design methods and tools that support a human designer in realizing such complex systems involving the material, product and manufacturing processes from a simulation-based design perspective. In this paper, we present a Goal-oriented Inverse Design method to achieve the integrated design exploration of materials, products and manufacturing processes. The key functionality offered is the capability to carry out a microstructure-mediated design satisficing specific processing requirements and performance goals of the product. Given models to establish the information flow chain, a designer can use the method for the decision-based design exploration of material microstructure and processing paths to realize products in a manufacturing process chain. The efficacy of the method is tested using an industry-inspired hot rolling problem to inversely design the thermo-mechanical processing of a steel rod. The focus here is the method and associated design constructs which are generic and support the formulation and decision-based design of similar problems involving materials, products and associated manufacturing processes.

Reconciling Co-Evolving Engineering and Customer Requirements With a Looped Bayesian Model

Engineering and manufacturing abilities of firms evolve with every passing year and so do the preferences of the customers buying their products. Reconciling this coevolution is essential to staying competitive in the marketplace. In this paper, we provide a looped Bayesian framework to accomplish this so that designs can evolve as engineering capabilities increase and customer preferences change. We begin with an approach to incorporating the voice of the customer through the multi-attribute utility function, the core of decision-based design. We consider the utility to be a stochastic function governed by shape parameters that are random variables. Typically, a representative preference or utility function is used or the function is aggregated over many decision makers and regarded as a deterministic function of specified shape parameters. In our approach, the shape parameters represent the stochastic nature of preference behavior either due to variation in a decision maker’s state of mind from one decision to another, or due to a multiplicity of decision makers. The novelty of this approach is in taking a Bayesian perspective on the stochastic utility function. We consider the utility distribution in the design phase as a prior distribution and we update the prior to a posterior with feedback on the actual product in production. The method is valuable in providing a means to improve the level of informativeness of the design level utility function for adjustments to the design or for the next design revision in the cycle of continuous improvement. We present our approach on a real-life assembly problem in an automotive manufacturing floor.

An Excess Based Approach to Change Propagation

This research demonstrates how the Decision Based Design (DBD) approach can be used for determining a system’s lifecycle value when including excess. Prior research has shown that excess (the degree to which a component or attribute is sized beyond the minimum required to support the initially fielded system) can reduce the cost of changing a system. Theoretically, excess inhibits change propagation within a system and could be strategically added to increase the value of that system. Including excess, however, also adds cost and potentially impacts system performance. Prior research has not quantitatively linked excess as a means of limiting change propagation to system lifecycle value. This work advances the existing literature by considering how excess is imbedded in a system and what impact excess has on the system’s total value. After being introduced, the method is demonstrated on a desktop computer example. Results from the study are used to show how decisions about power supply capacity can be optimized by incorporating excess to achieve flexibility.