An improved approach for automatic process plan generation of complex borings

The authors are grateful for funding provided to this project by the French Ministry of Industry, Dassault Aviation, Dassault Systemes, and F. Vernadat for his review and recommendations.The research concerns automated generation of process plans using knowledge formalization and capitalization. Tools allowing designers to deal with issues and specifications of the machining domain are taken into account. The main objective of the current work is to prevent designers from designing solutions that would be expensive and difficult to machine. Among all available solutions to achieve this goal, two are distinguished: the generative approach and the analogy approach. The generative approach is more adapted to generate the machining plans of parts composed of numerous boring operations in interaction. However, generative systems have two major problems: proposed solutions are often too numerous and are only geometrically but not technologically relevant. In order to overcome these drawbacks, two new concepts of feature and three control algorithms are developed. The paper presents the two new features: the Machining Enabled Geometrical Feature (MEGF) and the Machinable Features (MbF). This development is the result of the separation of the geometrical and the technological data contained in one machining feature. The second objective of the paper is to improve the current Process Ascending Generation (PAG) system with control algorithms in order to limit the combinatorial explosion and disable the generation of unusable or not machinable solutions

Tolerance analysis approach based on the classification of uncertainty (aleatory / epistemic)

Uncertainty is ubiquitous in tolerance analysis problem. This paper deals with tolerance analysis formulation, more particularly, with the uncertainty which is necessary to take into account into the foundation of this formulation. It presents: a brief view of the uncertainty classification: Aleatory uncertainty comes from the inherent uncertain nature and phenomena, and epistemic uncertainty comes from the lack of knowledge, a formulation of the tolerance analysis problem based on this classification, its development: Aleatory uncertainty is modeled by probability distributions while epistemic uncertainty is modeled by intervals; Monte Carlo simulation is employed for probabilistic analysis while nonlinear optimization is used for interval analysis.“AHTOLA” project (ANR-11- MONU-013

A Framework for Integration of Resource Allocation and Reworking Concept into Design Optimisation Problem

The life cycle of an assembled product faces various uncertainties considering the current state of the manufacturing line. Varied of activities are integrated with the manufacturing line including processing, inspection, reworking, assembly, etc. Therefore, any decision taken concerning each activity, will affect the end-product of the manufacturing line. In an early stage, designers define tolerances on parts to ensure the functionality of the end-product. In this regard, this paper integrates resource allocation (as a decision to assign practical resources to parts) and reworking decision (as a decision to improve parts conformity rate) into the tolerance allocation problem. A modular-based cost modelling approach is proposed objecting to minimisation of manufacturing cost concerning resource allocation and reworking decisions. Eventually, a genetic algorithm and Monte-Carlo simulation are adapted to analyse the applicability of the model

An improved approach for automatic process plan generation of complex borings

The authors are grateful for funding provided to this project by the French Ministry of Industry, Dassault Aviation, Dassault Systemes, and F. Vernadat for his review and recommendations.The research concerns automated generation of process plans using knowledge formalization and capitalization. Tools allowing designers to deal with issues and specifications of the machining domain are taken into account. The main objective of the current work is to prevent designers from designing solutions that would be expensive and difficult to machine. Among all available solutions to achieve this goal, two are distinguished: the generative approach and the analogy approach. The generative approach is more adapted to generate the machining plans of parts composed of numerous boring operations in interaction. However, generative systems have two major problems: proposed solutions are often too numerous and are only geometrically but not technologically relevant. In order to overcome these drawbacks, two new concepts of feature and three control algorithms are developed. The paper presents the two new features: the Machining Enabled Geometrical Feature (MEGF) and the Machinable Features (MbF). This development is the result of the separation of the geometrical and the technological data contained in one machining feature. The second objective of the paper is to improve the current Process Ascending Generation (PAG) system with control algorithms in order to limit the combinatorial explosion and disable the generation of unusable or not machinable solutions

Cost Estimation Method for Variation Management

International audienc

Meta-analysis of predictive models to assess the clinical validity and utility for patient-centered medical decision making: application to the CAncer of the Prostate Risk Assessment (CAPRA)

Background: The Cancer of the Prostate Risk Assessment (CAPRA) score was designed and validated several times to predict the biochemical recurrence-free survival after a radical prostatectomy. Our objectives were, first, to study the clinical validity of the CAPRA score, and, second, to assess its clinical utility for stratified medicine from an original patient-centered approach. Methods: We proposed a meta-analysis based on a literature search using MEDLINE. Observed and predicted biochemical-recurrence-free survivals were compared to assess the calibration of the CAPRA score. Discriminative capacities were evaluated by estimating the summary time-dependent ROC curve. The clinical utility of the CAPRA score was evaluated according to the following stratified decisions: active monitoring for low-risk patients, prostatectomy for intermediate-risk patients, or radio-hormonal therapy for high risk patients. For this purpose, we assessed CAPRA’s clinical utility in terms of its ability to maximize time-dependent utility functions (i.e. Quality-Adjusted Life-Years – QALYs). Results: We identified 683 manuscripts and finally retained 9 studies. We reported good discriminative capacities with an area under the SROCt curve at 0.73 [95%CI from 0.67 to 0.79], while graphical calibration seemed acceptable. Nevertheless, we also described that the CAPRA score was unable to discriminate between the three medical alternatives, i.e. it did not allow an increase in the number of life years in perfect health (QALYs) of patients with prostate cancer. Conclusions: We confirmed the prognostic capacities of the CAPRA score. In contrast, we were not able to demonstrate its clinical usefulness for stratified medicine from a patient-centered perspective. Our results also highlighted the confusion between clinical validity and utility. This distinction should be better considered in order to develop predictive tools useful in practice

An integrated resource allocation and tolerance allocation optimization: A statistical-based dimensional tolerancing

Today’s industrial world is facing rising demand for highly reliable and safe products. Complex industries, such as automobiles, medical, and aircraft, require a well-designed engineering plan which has a comprehensive understanding of the various certainties and uncertainties that occur in reality. Consequently, the need for reliable and precise parts has impacted the tolerancing activity. Key functions of complex products can often be realized by high precision part use. Thus, producers are confronted with high-quality requirements, cost pressure, and a rising number of demands. The introduction of new technologies and the need to meet the requirements have broadened the scope of tolerancing. In this paper, a statistical tolerance allocation model is developed to study the economic impact of allocated tolerances on an assembled product. The problem is aimed at optimizing the allocated tolerances to each part of the product while minimizing manufacturing costs. A modular cost model is proposed to determine the manufacturing costs related to each activity and part. The manufacturing costs include processing cost, inspection cost, scrap cost, assembly cost, and warranty cost. Furthermore, a genetic algorithm is adapted to study the applicability of the model developed on an exemplary assembled product

A new methodology to analyze the functional and physical architecture of existing products for an assembly oriented product family identification

In today’s business environment, the trend towards more product variety and customization is unbroken. Due to this development, the need of agile and reconfigurable production systems emerged to cope with various products and product families. To design and optimize production systems as well as to choose the optimal product matches, product analysis methods are needed. Indeed, most of the known methods aim to analyze a product or one product family on the physical level. Different product families, however, may differ largely in terms of the number and nature of components. This fact impedes an efficient comparison and choice of appropriate product family combinations for the production system. A new methodology is proposed to analyze existing products in view of their functional and physical architecture. The aim is to cluster these products in new assembly oriented product families for the optimization of existing assembly lines and the creation of future reconfigurable assembly systems. Based on Datum Flow Chain, the physical structure of the products is analyzed. Functional subassemblies are identified, and a functional analysis is performed. Moreover, a hybrid functional and physical architecture graph (HyFPAG) is the output which depicts the similarity between product families by providing design support to both, production system planners and product designers. An illustrative example of a nail-clipper is used to explain the proposed methodology. An industrial case study on two product families of steering columns of thyssenkrupp Presta France is then carried out to give a first industrial evaluation of the proposed approach

Reconfigurable machining process planning for part variety in new manufacturing paradigms: Definitions, models and framework

Conventional machining process planning approaches are inefficient to handle the process planning complexity induced by part variety. Reconfigurable process planning is a new process planning approach which has been well recognized as a key enabler for current manufacturing paradigms. However, in the literature, there is neither a comprehensive part variety representation model to support reconfigurable process planning nor a global solution framework to instruct the generation of the feasible process plans for a specific part variant. Therefore, this paper extends the concept of reconfigurable process planning to a concept of reconfigurable machining process planning which targets the process plan generation for a part family. A solution framework is developed for reconfigurable machining process planning. In this framework, a feature-based part variety model is proposed to represent a part family; A reconfigurable machining process plan is defined as a set of modular components which can be configured/reconfigured into the machining process plans for any part variant in the family; a novel configuration approach is proposed to generate the process plan components for a specific part variant while configuring this part variant from the family. The feasibility and effectiveness of the proposed framework and models are tested in a real case study

New product similarity index development with application to an assembly system typology selection

The choice of an adapted production system is essential in today’s volatile market environment. For this choice the identification of common and distinct assemblies in between the product variants is of high importance. This paper presents four new similarity indices which are aggregated to categorize products. The categorization will support the choice of an assembly system type (dedicated, reconfigurable or hybrid) for a selection of product subassemblies when designing a new production facility. On this way, operational areas for a reconfigurable system can be defined. The novel approach is applied to an industrial case study in automotive industry.European Regional Development Fund (“Programme opérationnel FEDER-FSE Lorraine et Massif de Vosges 2014-2020”