Yasser A. Hosni

Custom-designed orthopedic implants evaluated using finite element analysis of patient-specific computed tomography data: femoral-component case study.

BackgroundConventional knee and hip implant systems have been in use for many years with good success. However, the custom design of implant components based on patient-specific anatomy has been attempted to overcome existing shortcomings of current designs. The longevity of cementless implant components is highly dependent on the initial fit between the bone surface and the implant. The bone-implant interface design has historically been limited by the surgical tools and cutting guides available; and the cost of fabricating custom-designed implant components has been prohibitive.MethodsThis paper describes an approach where the custom design is based on a Computed Tomography scan of the patients joint. The proposed design will customize both the articulating surface and the bone-implant interface to address the most common problems found with conventional knee-implant components. Finite Element Analysis is used to evaluate and compare the proposed design of a custom femoral component with a conventional design.ResultsThe proposed design shows a more even stress distribution on the bone-implant interface surface, which will reduce the uneven bone remodeling that can lead to premature loosening.ConclusionThe proposed custom femoral component design has the following advantages compared with a conventional femoral component. (i) Since the articulating surface closely mimics the shape of the distal femur, there is no need for resurfacing of the patella or gait change. (ii) Owing to the resulting stress distribution, bone remodeling is even and the risk of premature loosening might be reduced. (iii) Because the bone-implant interface can accommodate anatomical abnormalities at the distal femur, the need for surgical interventions and fitting of filler components is reduced. (iv) Given that the bone-implant interface is customized, about 40% less bone must be removed. The primary disadvantages are the time and cost required for the design and the possible need for a surgical robot to perform the bone resection. Some of these disadvantages may be eliminated by the use of rapid prototyping technologies, especially the use of Electron Beam Melting technology for quick and economical fabrication of custom implant components.

Two-Party Negotiation Modeling: An Integrated Fuzzy Logic Approach

Game theoretic models attempted to predict unique equilibrium outcomes of negotiations with limited success. The imprecise character of negotiation is often altered to fit the game theorists exacting approach. Alternative models deviated from the formal game theoretic approach and attempted to accommodate concepts such as negotiator power and time pressure. In this paper, we introduce a model which uses a fuzzy logic approach to deal with the imprecision in the negotiation process and to integrate several negotiation theories. The new model is used to simulate multiple-issue, two-party negotiations and results are consistent with established negotiation theories.

Manufacturing lot-sizing under MRP II environment: an improved analytical model & a heuristic procedure

Under single-level lot-sizing problem, well known Wagner-Whitin algorithm based on Dynamic Programming (DP) provides optimal order schedule. Order schedule does not work properly under Manufacturing Resource Planning (MRP II), where it is considered multi-level capacitated problem and requirements of subcomponents are depend on the parent product. In this paper, we formulate a multi-level capacitated optimization model and develop a relatively efficient heuristic working under MRP II environment which considers work center capacities and interrelationship between levels in lot-sizing computation.

Laser based system for reverse engineering

Abstract The reverse engineering process involves the use of 3D data to manufacture a part. A crucial element in the reverse engineering process is obtaining 3D data of the part or its CAD model. The paper describes a laser-based system for reverse engineering. The laser scanning system performs the crucial role of capturing the geometric details of the object. This data can then be processed by routines to accurately define the object. This definition can then be used to manufacture a replica of the part or scaled object. Also addressed in the paper are issues for integrating the laser scanner with other stages in the product development and manufacturing cycle. This paper is an outcome of ongoing research aimed at manufacturing heat resistant tiles for the space shuttle to fit cavities created due to damaged or lost tiles after each space mission.

Rapid prototyping and tooling: A survey and applications

Publisher Summary With highly sophisticated computing power now available on the shop floor of production systems, new technologies are being introduced everyday. Among the emerging technologies that are making great strides toward reducing the cycle time in manufacturing is the areas of rapid prototyping (RP). RP is the process of rapid creation of a physical solid model (prototype) for an object from its design data without the use of tools or traditional manufacturing processes. The intent of this chapter is to provide an introduction to RP technologies, highlight the role of computers in making the technology feasible, and provide some results of applying the technology for the production of parts replacement in remote maintenance operations. This chapter discusses the technologies, namely, stereolithography, selective laser sintering, solid ground curing, fused decomposition modeling, and laminated object manufacturing. Rapid tooling techniques are discussed as an extension of rapid prototyping, though it is still at an experimental level. The application of the technologies involves the case of experimental rapid production of thermal tile replacements in the space shuttle.

Quality control & inspection: Knowledge-based quality control system

Abstract The majority of Statistical Quality Control (SQC) microcomputer systems/packages are based on the idea of storing data and producing results such as QC charts from which a user may be able to make inferences regarding Quality. The selection of the type of control charts (e.g. charts for variables vs. charts for attributes) and interpretation of the results are usually left to the user. This is mainly due to the fact that SQC packages are generic systems while interpretations may be product specific. Presented in this paper is a system which tries through dialogue with the user to direct him to the proper chart(s) in the package. An analysis component for each chart determines statistical phenomena (both good and bad) and provides general explanations. Another component in the system accesses an accompanying knowledge database (DB) — keyed by phenomena — which provide possible explanation as well as advise. The user may add to the knowledge base at any time assisted by the statistical DB Management Subsystem. The elements of the system are the IIE Microsoftware Statistical Quality Control package and a number of “add-on” routines supporting DB creation and the inference engine.

Knowledge-based quality control systems

Abstract The majority of Statistical Quality Control (SQC) microcomputer systems/packages are based on the idea of storing data and producing results such as QC charts from which a user may be able to make inferences regarding Quality. The selection of the type of control charts (e.g. charts for variables vs. charts for attributes) and interpretation of the results are usually left to the user. This is mainly due to the fact that SQC packages are generic systems while interpretations may be product specific. Presented in this paper is a system which tries through dialogue with the user to direct him to the proper chart(s) in the package. An analysis component for each chart determines statistical phenomena (both good and bad) and provides general explanations. Another component in the system accesses an accompanying knowledge database (DB) — keyed by phenomena — which provide possible explanation as well as advise. The user may add to the knowledge base at any time assisted by the statistical DB Management Subsystem. The elements of the system are the IIE Microsoftware Statistical Quality Control package and a number of “add-on” routines supporting DB creation and the inference engine.

Inference engine for material handling selection

Abstract In this paper we describe the inference engine of an expert system for material handling method and equipment selection. The system branches through a tree guided by collected data essential for solving the material handling equation: Material + Move → Method. The equation is solved using rules developed to handle relationships between elements and factors of the equation. While the engine in its current status is limited to a “ first cut” in the equipment selection process, it is of value to nonspecialist industrialist. Plans are for the final system to provide its user with access to vendors specialized in particular handing operations.

Capacity planning in job-shop environment

Abstract Presented here is a computerized capacity planning system for the IBM Microcomputer family. The system maintains the profile of the job shop in a data base along with data pertinent to various products that can be manufactured in the shop. Projected orders for the planning period are input to the system with their associated quantities and delivery dates. The system uses the forward and backward loading rules in generating capacity loading scenarios. User selects the best course of action which may satisfy delivery dates subject to the limitations of the work centers. Efficiency figures are provided to aid the user in his/her decision.

Sensitivity analysis for multi-variable models: Methodology and application for the economics of energy management systems

Abstract A method has been developed enabling analysts to measure the sensitivity of model outcome for a large number of variables. Variables are classified as direct or indirect based on their relationship to the model output. The method involves building an interface between the indirect variables and the direct ones and modifying a basic model before measuring the sensitivity of the model for a given variable. Sensitivity is measured through the computation of the model value; each time a variable is assigned a new value between predetermined limits. The method was formulated analytically and a computer program written to facilitate using the models for survey purposes as well as sensitivity analysis depending on the application.