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The concept of a Quality System’s approach to business has been employed successfully and sometimes not so successfully for several decades. The International Organization for Standardization (ISO) has been supplying standards that list the key elements/clauses and requirements for building and implementing Quality Systems for over 30 years. These standards are based on the relatively simple concepts of Total Quality Management (TQM), essential principals of management, and a “Process” approach. These standards have been revised several times over the years to make them more realistic and user friendly.

This course is offered in China only and presented in Mandarin Chinese. The course materials are bilingual (English and Chinese). Currently in the industry, especially within China, product requirement development is more of an experience-based process rather than a scientific methodology. This course addresses this issue and provides a more process-driven method for better requirement development through the Quality Function Deployment (QFD) methodology.  Real industrial examples are used to demonstrate how to systematically convert the voice of the customer data to engineering specifications using QFD.

The Process FMEA and Control Plan program introduces the basic concepts behind this important tool and provides training in how to conduct an effective PFMEA. First, the course explains what a PFMEA is and how it improves the long-term performance of your products, services and related processes by addressing process related failures. The role of the PFMEA in the overall framework of Quality Management System Requirements is explained as well as the role of the PFMEA in the Advanced Product Quality Planning (APQP) process. Additionally, the differences and relationships between the DFMEA and PFMEA are well defined.

During this DFMEA Overview and Application course, participants will be introduced to important FMEA concepts, the basic theory behind the concepts, then discuss how these concepts can be applied to the customer's design FMEA activities. Participant activities include: reading assignments, group discussions, exercises, building Block Diagrams as a group, and beginning a DFMEA on a customer’s product.

Design of Experiments is a statistically based, structured approach to product or process improvement that will quickly yield significant increases in product quality and subsequent decreases in cost.  Products and processes can be designed to function with less variation and with less sensitivity to environmental factors or customer usage. While still maintaining high quality from a customer's viewpoint, products and processes can utilize lower cost materials and methods.  Specifications can be opened-up with wider tolerances while still maintaining high quality for customers.  

This course is verified by Probitas as meeting the AS9104/3A requirements for Continuing Professional Development. Advanced product quality planning (APQP) is essential to improving the way companies develop products and services.  It is a standardized, universally accepted fundamental business strategy. This strategy is applicable to all types of organizations including manufacturing and service companies, schools, hospitals, and governmental agencies. The aim of APQP is to enable the organization to produce products and provide services focused on satisfying customer’s needs, wants, and expectations.  

Design of Experiments (DOE) is a methodology that can be effective for general problem-solving, as well as for improving or optimizing product design and manufacturing processes. Specific applications of DOE include identifying proper design dimensions and tolerances, achieving robust designs, generating predictive math models that describe physical system behavior, and determining ideal manufacturing settings. This course utilizes hands-on activities to help you learn the criteria for running a DOE, the requirements and pre-work necessary prior to DOE execution, and how to select the appropriate designed experiment type to run.

RMS (Reliability-Maintainability-Safety-Supportability) engineering is emerging as the newest discipline in product development due to new credible, accurate, quantitative methods. Weibull Analysis is foremost among these new tools. New and advanced Weibull techniques are a significant improvement over the original Weibull approach. This workshop, originally developed by Dr. Bob Abernethy, presents special methods developed for these data problems, such as Weibayes, with actual case studies in addition to the latest techniques in SuperSMITH® Weibull for risk forecasts with renewal and optimal component replacement.

Abstract Reliability analysis of a large-scale system under random dynamic loads can be a very time-consuming task since it requires repeated studies of the system. In many engineering problems, for example, wave loads on an offshore platform, the excitation loads are defined using a power spectral density (PSD) function. For a given PSD function, one needs to generate many time histories to make sure the excitation load is modeled accurately. Global and local approximation methods are available to predict the system response efficiently. Each way has their advantages and shortcomings. The combined approximations (CA) method is an efficient method, which combines the advantages of local and global approximations. This work demonstrates two methodologies that utilize CA to reduce the cost of crude or separable Monte Carlo simulation (MCS) of linear dynamic systems when the excitation loads are defined using PSD functions.

Road vibrations cause fatigue failures in vehicle components and systems. Therefore, reliable and accurate damage and life assessment is crucial to the durability and reliability performances of vehicles, especially at early design stages. However, durability and reliability assessment is difficult not only because of the unknown underlying damage mechanisms, such as crack initiation and crack growth, but also due to the large uncertainties introduced by many factors during operation. How to effectively and accurately assess the damage status and quantitatively measure the uncertainties in a damage evolution process is an important but still unsolved task in engineering probabilistic analysis. In this paper, a new procedure is developed to assess the durability and reliability performance, and characterize the uncertainties of damage evolution of components under constant amplitude loadings.

This paper focuses on the manufacturer's conflict in the conceptual design of commercial vehicles between highly customized special vehicles and the greatest possible degree of standardization. Modularity and standardization are crucial success factors for realizing high variance at the best cost efficiency in development and production as well for achieving the highest quality standards at reduced efforts for technical validation. The presented virtual design approach for commercial vehicle concepts allows for purposeful design and integration of new concepts and technologies on the component level in an existing product portfolio - not neglecting manufacture's portfolio requirements concerning standardization and modularity. The integrated tool chain helps to bring trade-offs to a head that exist in balancing between dedicated vehicles with best customer-relevant characteristics and standardized vehicles with the highest degree of commonality.

Compared to the vehicles with conventional steering, the articulated frame steer vehicles (ASV) are known to exhibit lower directional and roll stability limits. Furthermore, the tire interactions with relatively rough terrains could adversely affect the directional and roll stability limits of an ASV due to terrain-induced variations in the vertical and lateral tire forces. It may thus be desirable to assess the dynamic safety of ASVs in terms of their directional control and stability limits while operating on different terrains. The effects of terrain roughness on the directional stability limits of an ASV are investigated through simulations of a comprehensive three-dimensional model of the vehicle with and without a rear axle suspension. The model incorporates a torsio-elastic rear axle suspension, a kineto-dynamic model of the frame steering struts and equivalent random profiles of different undeformable terrains together with coherence between the two tracks profiles.

Agriculture Tractors are widely used as prime mover either to pull or drive the “Implements” in the farms, apart from custom made equipments like Transplanter, Manure Spreader, Combine Harvester, Cotton Picker, mobile irrigation etc. which are used for particular operations in large production capacities. For larger landholdings, timely completion of the operation within the window period is the major decisive factor that drives agriculture tractor design. For small farms like in India, the productivity requirement was offset by the versatility of the equipment. Also, the farming practice varies in India due to geographical conditions such as soil types and demographic conditions such as crops types. Hence, the mechanisation level of matured market was not yet achieved in India, though the technologies are available for implementation.

To improve overall customer experience, it is imperative to minimize the noise levels inside agricultural equipment cab. Up-front prediction of acoustic performance in product development is critical to implement the noise control strategies optimally. This paper discusses the methodology used for virtual modeling of a cab on agricultural equipment for prediction of interior noise. The Statistical Energy Analysis (SEA) approach is suitable to predict high frequency interior noise and sound quality parameters such as articulation index and loudness. The cab SEA model is developed using a commercial software. The structural and acoustic excitations are measured through physical testing in various operating conditions. The interior noise levels predicted by the virtual model are compared with the operator ear noise levels measured in the test unit. The resultant SPL spectrum from SEA correlates well with the test.

The evolution of engine technology has so far seen the most beneficial side of progress in the fields of transportation, agriculture, and mobility. With the advent of innovation, there is also an impact on our environment that needs to be balanced. This is where fuels like CNG, LPG, LNG, etc. outperform conventional fossil fuels in terms of pollution & operational cost. This paper enlightens on the use of innovative dual-fuel technology where diesel & CNG fuels are used for combustion simultaneously inside the combustion chamber. Dual fuel system adaptation for farm application ensures self-reliance of the farmer where he can generate Bio-CNG to use the renewable fuel for farming making him less dependent on conventional fossil fuel thus promoting a green economy. The dual-fuel system is adapted to the existing in-use diesel engine with minimum modifications. This makes it feasible to retrofit a CNG fuel system on an existing diesel engine to operate it on dual fuel mode.

Due to recent infrastructural development and emerging competitive automotive markets, there is seen a huge shift in customer’s demand and vehicle drivability pattern in commercial vehicle industry. Now apart from ensuring better vehicle durability and best in class tyre life and fuel mileage, a vehicle manufacturer also has to focus on other key attributes like driver’s safety and ride comfort. Thus, for ensuring enhanced drivability, key parameters for ensuring better vehicle handling includes optimization of bump steer and brake steer. Both bump steer and brake steer are vehicle’s undesirable phenomenon where a driver is forced to constantly make steering wheel correction in order to safely maneuver the vehicle in the desired path.

This paper discusses the development of an all speed governed diesel-natural gas dual fuel engine for agricultural farm tractor. A 45 hp, 2.9 liters diesel-natural gas dual fuel engine with a novel closed loop secondary fuel injection system was developed. A frugal approach without any modification of the base mechanical diesel fuel injection system was followed. This approach helped to minimize the cost impact, while meeting performance and emissions at par with neat diesel operation. Additional cost on gas injection system is redeemed by cost savings on diesel fuel. The dual fuel technology developed by Mahindra & Mahindra Ltd., substitutes on an average approximately 40% of diesel with compressed natural gas, meeting the TREM III A emission norms for dual fuel while meeting all application requirements. The governing performance of the tractor was found to be superior than base diesel tractor.