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 organized 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

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

Intelligent feature based resource selection and process planning

Lien vers la version éditeur: https://www.inderscience.com/books/index.php?action=record&rec_id=755&chapNum=3&journalID=1022&year=2010This paper presents an intelligent knowledge-based integrated manufacturing system using the STEP feature-based modeling and rule based intelligent techniques to generate suitable process plans for prismatic parts. The system carries out several stages of process planning, such as identification of the pairs of feature/tool that satisfy the required conditions, generation of the possible process plans from identified tools/machine pairs, and selection of the most interesting process plans considering the economical or timing indicators. The suitable processes plans are selected according to the acceptable range of quality, time and cost factors. Each process plan is represented in the tree format by the information items corresponding to their CNC Machine, required tools characteristics, times (machining, setup, preparatory) and the required machining sequences. The process simulation module is provided to demonstrate the different sequences of machining. After selection of suitable process plan, the G-code language used by CNC machines is generated automatically. This approach is validated through a case

The Effectiveness of Group Logotherapy in Increasing Resilience and Decreasing Depression among Individuals Affected by Substance Abuse in Tehran

Introduction: Substance use disorder is one of the chronic and often recurrent disorders that predispose a person to serious problems, such as AIDS, hepatitis and other chronic disorders. This study aimed to determine the effectiveness of group logotherapy in increasing resilience and decreasing depression among individuals with addiction in Tehran. Method: Semi-experimental research method with pre-test, post-test design and control group was utilized in this study. The statistical population of this study included all individuals affected by substance abuse referred to drug rehabilitation clinic in Tehran. The sample consisted of 36 individuals with substance abuse; whose depression and resilience scores were as much as two standard deviations lower than the mean. Subjects were randomly assigned to experimental and control groups. Beck Depression Inventory and Caner-Davidson’s Resilience Questionnaire were adopted. Ten 90-minute group logotherapy sessions were held for the experimental group. Data were analyzed using multivariate covariance method. Results: The findings of this study indicated that group logotherapy, increased resilience and decreased depression in the experimental group. Conclusion: Logotherapy can be considered as a new way of introducing purposefulness and meaningfulness in life. It increases the level of resilience and increase happiness for patients with substance abuse through assisting them in discovering their real self, selecting individual values, and finding the meaning of life. Declaration of Interest: None

The Response Modification Factor for Seismic Design of Integral Abutment Bridges

The response modification factor (R factor) is a crucial parameter for calculating the design seismic forces applied to a bridge structure. This factor considers the nonlinear performance of bridges during strong ground motions. Conventional bridge structures rely on the substructure components to resist earthquake forces. Accordingly, there are R factors available in the design codes based on the type of bridge substructure system. Lateral load resisting system of Integral Abutment Bridges (IABs) in the longitudinal direction is more complex than ordinary bridges. It involves the contributions from soils behind the abutments and soil/structure interaction (SSI) in addition to existing rigid connection between the superstructure and abutments. There is no R factor available in any design code throughout the world for IABs in the longitudinal direction that considers all these parameters. In this research, the Federal Emergency Management Agency publication  FEMA P695 methodology has been applied to estimate the R factor for IABs. It is found that 3.5 could be a safe and valid R factor in the longitudinal direction for seismic design of such bridges

Proposition d'une méthodologie de modélisation géométrique en contexte collaboratif

Today, Internet technology proposes communication, exchange and data storage powerful tools. They are standardized and accessible to the companies. But usually, they are not adapted for a mechanical design use and they do not take into account the design process. So, in this context, we present a method allowing the definition of real needs for collaborative engineering in terms of creation, management and exchange of technical data and more specially, geometrical data. From the results of this analysis, we propose a model on which is based a geometrical modelling methodology for mechanical products in a integrated design and collaborative engineering context

The study of essential oil composition of Matricaria chamomilla in Khouzestan

Background and aims: Matricaria chamomilla is an important medicinal plant that widely is used in pharmaceuticals and food industries. The present study was aimed to evaluate the essential oil composition of samples of Matricaria chamomilla collected from different regions of Khouzestan. Methods: In this experimental study, samples of Matricaria chamomilla were collected from different regions of Khuzestan at full flowering stage. The component identification was achieved by the Gas chromatography–mass spectrometry (GC-MS) analysis. Total GC running time was 75 min. The components of essential oil were identified on the basis of comparison of their retention time and mass spectra with published data. Moreover, they were identified by computer matching with Wiley 7n, National Institute of Standards and Technology (NIST) libraries provided with computer controlling the GC-MS system, and Adams book in Centrallab of Agriculture and Natural Resources University of Khuzestan. Results: The main oil compounds of samples of Matricaria chamomilla were α-Pinene, Sabinene, β-Pinene, 1,8-Cineole, Citronellol, Aromadendrone, (E).β-farnesene, Spathulenol, Caryophyllene oxide, α-Bisabolone oxide A, α-Bisabolole oxide B, Chamazolene and α-Bisabolole oxide A, collected from different regions of Khouzestan. Also, α-Bisabolone oxide A, Caryophyllene oxide, Chamazolene and α-Bisabolole oxide A were the highest percentage of the main oil compounds of these samples. Conclusions: The Caryophyllene oxide, α-Bisabolone oxide A, Chamazolene, α-Bisabolole oxide A are dominant components in the essential oil of Matricaria chamomilla in weather and geographical conditions of studied samples and different climates are effective on plant essential oil composition

Improving on-farm agricultural water productivity in the Karkheh River Basin

Improving On-farm Agricultural Water Productivity in the Karkheh River Basin (KRB) was a CPWF project that aimed at enhancement of agricultural water productivity (WP) under irrigated and rainfed conditions in Karkheh River Basin. It was launched in Iran through the partnership of ICARDA and the Iranian NARES under the Agricultural Extension, Education, and Research Organization. The project lasted for more than four years between 2004 and 2008. Whereas capacity building was an important part of the agenda, PN8 was a participatory, multi-disciplinary, and action-oriented project that carried out mostly on-farm trials. Findings included existing crop water productivity, suitable technologies for their improvement, interactions between the upper and lower KRB, and a review of the prevailing water policies and institution