Plant-Limited Co-Design of an Energy-Efficient Counterbalanced Robotic Manipulator

Modifying the design of an existing system to meet the needs of a new task is a common activity in mechatronic system development. Often engineers seek to meet requirements for the new task via control design changes alone, but in many cases new requirements are impossible to meet using control design only; physical system design modifications must be considered. Plant-Limited Co-Design (PLCD) is a design methodology for meeting new requirements at minimum cost through limited physical system (plant) design changes in concert with control system redesign. The most influential plant changes are identified to narrow the set of candidate plant changes. PLCD provides quantitative evidence to support strategic plant design modification decisions, including tradeoff analyses of redesign cost and requirement violation. In this article the design of a counterbalanced robotic manipulator is used to illustrate successful PLCD application. A baseline system design is obtained that exploits synergy between manipulator passive dynamics and control to minimize energy consumption for a specific pick-and-place task. The baseline design cannot meet requirements for a second pick-and-place task through control design changes alone. A limited set of plant design changes is identified using sensitivity analysis, and the PLCD result meets the new requirements at a cost significantly less than complete system redesign.

Optimum Design of Columns Under Elastic Buckling

In this paper, a generalized approach is developed to optimize column configuration subjected to buckling load. The configuration utilizes B-spline contour to provide more freedom to model the column shape. Previous columns in literature use tapered or parabolic tapered for configuration. This work considers hinged-hinged columns of circular solid cross-sectional area. Two sample applications are optimized using Genetic Algorithm with the finite difference method to satisfy the buckling constraints. The length and load are fixed. The objective is to minimize the volume considering the cross-sectional diameters as the design variables. B-Spline quadratic with three and five control points and cubic with five control points are applied. The proposed configuration is compared with tapered and parabolic tapered columns. Results show that continuity provides a better optimum against column buckling than other tapered columns. Even though volume is more than some configurations by about 1.67%, but those configurations would not satisfy buckling constraints over the entire length of the column.

Identifying Key Product Attributes and Their Importance Levels From Online Customer Reviews

Identifying customer needs and preferences is one of the most important tasks in design process. Typically, a variation of interview based approaches is used to conduct need and preference analysis. In this paper, a new approach based on text mining online (internet based) customer reviews to supplement traditional methods of need and preference analysis is considered. The key idea underlying the proposed approach is to partition online customer generated product reviews into segments that evaluate the individual attributes of a product (e.g zoom capability and support of different image formats in a camcorder). Additionally, the proposed method also identifies the importance (ranking) that customers place on each product attributes. The method is demonstrated on 100 customer reviews submitted for camcorders on epinions.com over a two year period.

Enabling Decision-Based Design Using Solution Trajectory Correction and Backtracking Rules

Optimization is needed for effective decision based design (DBD). However, a utility function assessed a priori in DBD does not usually capture the preferences of the decision maker over the entire design space. As a result, when the optimizer searches for the optimal design, it traverses (or ends up) in regions where the preference order among different solutions is different from the actual order. For a highly non-convex design space, this can lead to convergence to a grossly suboptimal design depending on the initial design. In this article, we propose two approaches to alleviate this issue. First, we map the trajectory of the solution as generated by the optimizer and generate ranking questions that are presented to the designer to verify the correctness of the utility function. We then propose backtracking rules if a local utility function is very different from the initially assessed function. We demonstrate our methodology using a mathematical example and a welded beam design problem.

PSS Business Case Map: Supporting Idea Generation in PSS Design

This paper proposes the PSS Business Case Map as a tool to support designers’ idea generation in PSS design. The map visualizes the similarities among PSS business cases in a two-dimensional diagram. To make the map, PSS business cases are first collected by conducting, for example, a literature survey. The collected business cases are then classified from multiple aspects that characterize each case such as its product type, service type, target customer, and so on. Based on the results of this classification, the similarities among the cases are calculated and visualized by using the Self-Organizing Map (SOM) technique. A SOM is a type of artificial neural network that is trained using unsupervised learning to produce a low-dimensional (typically two-dimensional) view from high-dimensional data. The visualization result is offered to designers in a form of a two-dimensional map, which is called the PSS Business Case Map. By using the map, designers can figure out the position of their current business and can acquire ideas for the servitization of their business.

Topology Optimization of Blank Geometry for the Sheet Forming Process

The newly developed element exchange method (EEM) for topology optimization is applied to the problem of blank shape optimization for the sheet-forming process. EEM uses a series of stochastic operations guided by the structural response of the model to switch solid and void elements in a given domain to minimize the objective function while maintaining the specified volume fraction. In application of EEM to blank optimization, a sheet forming simulation model is developed using Abaqus/Explicit. With the goal of minimizing the variability in wall thickness of the formed component, a subset of solid (i.e., high density) elements with the highest increase in thickness is exchanged with a consistent subset of void (i.e., low density) elements having the highest decrease in thickness so that the volume fraction remains constant. The EEM operations coupled with finite element simulations are repeated until the optimum blank geometry (i.e., boundary and initial thickness) is found. The developed numerical framework is applied to blank optimization of a benchmark problem. The results show that EEM is successful in generating the optimum blank geometry efficiently and accurately.

Pre-Life and End-of-Life Combined Profit Optimization With Predictive Product Lifecycle Design

The Predictive Product Lifecycle Design (PPLD) model that is proposed in this paper enables a company to optimize its product lifecycle design strategy by considering pre-life and end-of-life at the initial design stage. By combining lifecycle design and predictive trend mining technique, the PPLD model can reflect both new and remanufactured product market demands, capture hidden and upcoming trends, and finally provide an optimal lifecycle design strategy in order to maximize profit over the span of the whole lifecycle. The outcomes are lifecycle design strategies such as product design features, the need for buy-backs at the end of its life, and the quantity of products remanufacturing. The developed model is illustrated with an example of a cell phone lifecycle design. The result clearly shows the benefit of the model when compared to a traditional Pre-life design model. The benefit would be increased profitability, while saving more natural resources and reducing wastes for manufacturers own purposes.

A Case Study of the Implementation and Maintenance of a Fee for Service Lighting System for a Rural Village in Sub Saharan Africa

Electricity is a critical need for the rural poor in developing countries. Often this need is met with disposable batteries. This results in high cost and problems with disposal. For example it was recently reported that an isolated rural village in West Africa with a population of 770 uses more than 21,000 disposable batteries per year and that purchase of these batteries accounts for 20–40% of household expense. As a result many organizations are seeking way to meet the need for village energy. This paper presents a case study of one such experience. In this study the efforts to meet the lighting needs of a cluster of eight rural villages with a population of approximately 8,000 people are discussed. A key aspect of this discussion is the challenge of creating a continuing and sustainable village lighting solution. In this case the technology chosen to implement a lighting system was a distributed micro-grid managed locally in each village. The success of this lighting grid has been in large part due to the continuing support of the local micro-grid system both financially and through continued engagement to maintain and upgrade the micro-grid systems.

Coordination of Product Design Process in View of Product and Organizational Structures

Management of product design projects becomes increasingly difficult as the complexity of products increases. For better management of such projects, well-considered preliminary coordination of design processes is essential. This paper proposes a method for coordination in the design process, which comprises two phases: 1) division of the design work into smaller tasks and sequencing them and 2) establishment of management activities. To facilitate this coordination, an integrated model of a product, process, and organization is proposed. The division and sequencing of design tasks is based upon analysis of the product model. The method utilizes rational prioritization of design parameters, which means identification of parameters that must be first considered for changes. The resulting design processes can show where coordination among design tasks is needed. This, in turn, implies the necessity of management. It is preferable for a different style of management to be adopted for each part. Here, the importance of management and organizational structure prescribe the style of management that should be adopted. In this paper, two approaches to management are discussed: 1) the formation of a pre-agreement, and 2) integration and after-approval. Throughout the paper, the example of a solar boat design is used to explain how the proposed method works and to demonstrate its feasibility.

A Hybrid Inference Approach for Health Diagnostics With Unexampled Faulty States

System health diagnostics provides diversified benefits such as improved safety, improved reliability and reduced costs for the operation and maintenance of engineered systems. Successful health diagnostics requires the knowledge of system failures. However, with an increasing complexity it is extraordinarily difficult to have a well-tested system so that all potential faulty states can be realized and studied at product testing stage. Thus, real time health diagnostics requires automatic detection of unexampled faulty states through the sensory signals to avoid sudden catastrophic system failures. This paper presents a hybrid inference approach (HIA) for structural health diagnosis with unexampled faulty states, which employs a two-fold inference process comprising of preliminary statistical learning based anomaly detection and artificial intelligence based health state classification for real time condition monitoring. The HIA is able to identify and isolate the unexampled faulty states through interactively detecting the deviation of sensory data from the known health states and forming new health states autonomously. The proposed approach takes the advantages of both statistical approaches and artificial intelligence based techniques and integrates them together in a unified diagnosis framework. The performance of proposed HIA is demonstrated with a power transformer and roller bearing health diagnosis case studies, where Mahalanobis distance serves as a representative statistical inference approach.