Alain Etienne

Improved algorithm for tolerance allocation based on Monte Carlo simulation and discrete optimization

The allocation of design and manufacturing tolerances has a significant effect on both manufacturing cost and quality. This paper considers nonlinearly constrained tolerance allocation problems. The purpose is to minimize the ratio between the sum of the manufacturing costs (tolerances costs) and the risk (probability of the respect of geometrical requirements). The techniques of Monte Carlo simulation and genetic algorithm are adopted to solve these problems. As the simplest and the popular method for non-linear statistical tolerance analysis, the Monte Carlo simulation is introduced into the frame. Moreover, in order to make the frame efficient, the genetic algorithm is improved according to the features of the Monte Carlo simulation. An illustrative example (hyperstatic mechanism) is given to demonstrate the efficiency of the proposed approach.

VR-PMS: a new approach for performance measurement and management of industrial systems

A new performance measurement and management framework based on value and risk is proposed. The proposed framework is applied to the modelling and evaluation of the a priori performance evaluation of manufacturing processes and to deciding on their alternatives. For this reason, it consistently integrates concepts relevant to objectives, activity, and risk in a single framework comprising a conceptual value/risk model, and it conceptualises the idea of value- and risk-based performance management in a process context. In addition, a methodological framework is developed to provide guidelines for the decision-makers or performance evaluators of the processes. To facilitate the performance measurement and management process, this latter framework is organised in four phases: context establishment, performance modelling, performance assessment, and decision-making. Each phase of the framework is then instrumented with state-of-the-art quantitative analysis tools and methods. For process design and evaluation, the deliverable of the value- and risk-based performance measurement and management system (VR-PMS) is a set of ranked solutions (i.e. alternative business processes) evaluated against the developed value and risk indicators. The proposed VR-PMS is illustrated with a case study from discrete parts manufacturing but is indeed applicable to a wide range of processes or systems.

Specifications and development of interoperability solution dedicated to multiple expertise collaboration in a design framework

This paper describes the specifications of an interoperability platform based on the Product Process Organization (PPO) model developed by the French community IPPOP in the context of collaborative and innovative design. By using PPO model as a reference, this work aims to connect together heterogonous tools used by experts easing data and information exchanges. After emphasising the growing needs of collaborative design process, this paper focuses on interoperability concept by describing current solutions and their limits. Then a solution based on the flexibility of the PPO model adapted to the philosophy of interoperability is proposed. To illustrate these concepts, several examples are presented (robustness analysis, CAD and product lifecycle management systems connections).

Decision-making in the manufacturing environment using a value-risk graph

A value-risk based decision-making tool is proposed for performance assessment of manufacturing scenarios. For this purpose, values (i.e. qualitative objective statements) and concerns (i.e. qualitative risk statements) of stakeholders in any given manufacturing scenario are first identified and are made explicit via objective and risk modeling. Next, performance and risk measures are derived from the corresponding objective and risk models to evaluate the scenario under study. After that, upper and lower bounds, and target value is defined for each measure in order to determine goals and constraints for the given scenario. Because of the multidimensionality nature of performance, the identified objectives and risks, and so, their corresponding measures are usually numerous and heterogeneous in nature. These measures are therefore consolidated to obtain a global performance indicator of value and global indicator of risk while keeping in views the inter-criteria influences. Finally, the global indicators are employed to develop minimum acceptable value and maximum acceptable risk for the scenario under study and plotted on the VR-Graph to demarcate zones of “highly desirable”, “feasible”, “and risky” as well as the “unacceptable” one. The global scores of the indicators: (value-risk) pair of the actual scenario is then plotted on the defined VR-Graph to facilitate decision-making by rendering the scenarios’ performance more visible and clearer. The proposed decision-making tool is illustrated with an example from manufacturing setup in the process context but it can be extended to product or systems evaluation.

(Value, Risk)-based Performance Evaluation of Manufacturing Processes

A value/risk -based performance evaluation framework is proposed in the context of manufacturing processes at the industrialization phase of product development. Various risk factors of the manufacturing process are identified through Failure Mode and Effect Analysis (FMEA) and then embedded in the process plan models. Modelling and simulation are then employed for determining the value a process plan can create and the risk it is exposed to. Alternative scenarios are developed, simulated and compared with a reference scenario. The methodology is illustrated with a case study issued from parts manufacturing but is applicable to a wide range of other processes.

Process-oriented risk assessment methodology for manufacturing process evaluation

A process-oriented quantitative risk assessment methodology is proposed to evaluate risk associated with processes using modelling, simulation and decision-making approaches. For this purpose, risks involved in a process and the corresponding risk factors are identified through an objective-oriented risk identification approach. The identified risks are first analysed qualitatively in the failure mode effect and critical analysis process and then evaluated quantitatively in a simulation environment employing a process-based risk measurement model. To ease the decision-making process in case of multiple but heterogeneous risk measures, a global risk indicator is developed using the normalisation and aggregation techniques of the decision theory. Using the proposed methodology as a decision-making tool, alternative manufacturing scenarios (i.e. manufacturing process plans) are developed and ranked on the basis of desirability. Although the methodology is illustrated with a case study issued from the part manufacturing, it is also applicable to a wide range of other processes.

Activity-Based Tolerance Allocation (ABTA) – driving tolerance synthesis by evaluating its global cost

This paper deals with tolerance allocation driven by an activity-based approach. Its main objective is to rationally give a good indicator of the relevance of tolerance values fixed by designers. Taking into consideration the impacts of tolerance allocation on the manufacturing process and so the production cost, several examples are given to illustrate this concept. Moreover this paper deals with how the geometrical analysis can be carried out in this activity framework, illustrated by several industrial cases. In addition, this paper explains how, coupled with an optimisation algorithm, this method can generate the best compromise between cost and high performance. To illustrate the efficiency of this approach and its realisation, models and user interfaces based on an industrial case are given.

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

Abstract 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.

Safety of Manufacturing Equipment: Methodology Based on a Work Situation Model and Need Functional Analysis

The aim of “integrated prevention” is to conduct a preliminary risk analysis in order to achieve a lower level of risk in the design of future work equipment. Despite the many safety documents that exist, many companies, particularly SME/SMIs, do not yet apply these safe design principles. Integration of safety in the design process is mainly based on the individual knowledge or experience of the designers and is not conducted in any formalized way. In order to answer to this problem, this paper presents a methodology to involve engaging stakeholders in dynamic dialogue and a framework so that they may together define the information necessary for implementing safe design principles during the functional specification. The proposed methodology has been validated to industrial case.

Multi-criteria performance management methodology for decision support in industrial project selection problems

Selecting the most adapted alternative for a new project is a challenging problem because it contains a lot of uncertainty due to lack of information. Moreover, better decision making processes still need to be proposed to help decision makers to select the most effective solution among several alternatives. Although different methods and tools have been developed for this purpose, there is still room for improvement. Therefore, the objective of this paper is to develop a methodology that provides the decision makers with comprehensive and accurate performance expressions for decision support in project selection problems. The proposed methodology consists of three main phases: performance criteria identification, performance quantification and aggregation based on the following performance dimensions: benefit, cost, value and risk.