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Diesel injection equipment is required to be more accurate and higher in pressure to meet the increasingly strict emission, fuel consumption regulations and higher engine performance. It also needs to achieve a number of requirements such as robustness against diversified market fuels, easy installation to engine, etc.

A transformation of agriculture reached commercial reality at the beginning of this century as automated steering of agricultural machine systems increased the productivity and convenience in crop production systems. Following guidance, additional technologies have resulted in increasing optimized machine productivity. Today, integrated worksite solutions through machine and information management continues to transform agriculture. This is the precursor to autonomous worksite solutions that lead to the optimization of the worksite ecosystem. This paper will review the progress from the perspective of the customer value provided by increasing automated systems and the industry execution of autonomous driving technologies and will enable the pathways to autonomous worksites.

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.

A typical cab used on agriculture machines is made up of a metal frame structure with large enclosing panels of glass, plastic, and metal. Acoustic treatments such as coatings, textiles and foams are used within the cab for aesthetics but also to mediate undesired noise. To develop effective designs for the cab to combat noise, accurate tools for measurement, and predictive methods for sound transmission loss are needed. This paper focuses on Sound Transmission Loss (STL) of the rear upper panel of a cab used in agriculture machines. Results from CAE based tools such as Statistical Energy Analysis (SEA), Finite Element Analysis (FEA) and Hybrid FE-SEA methods are compared to measurements. The panel studied included features such as curvature, deep drawn beads with a glass window and a damping coating. The simulation results are refined by incorporating methods for accurate modeling of ribs stiffness, curvature effect and radiation efficiency by synthetic modal approach.

Light-weight 3-D models offer improved communication and visualization for advertising, marketing, service technicians, suppliers and other business partners. These models also may be a ready source of geometry and a window into a company's intellectual property for miscreants seeking to pirate designs and to produce counterfeit or will-fit parts. What approaches and tools are available to help protect a company's intellectual property while enabling it and its business partners to benefit from widespread distribution of 3-D animations and models? How should they be applied to effectively protect intellectual property? This paper provides a general survey of techniques available for protecting intellectual property in 3-D models when sending these files outside of a company and into broad distribution.