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Purpose. To evaluate the effects of different placements of mesial implants and different angles of distant implants in maxillary edentulous jaws on the stress on the implant and the surrounding bone tissue under dynamic loading. Materials and Methods. Cone beam computed tomography was used to acquire images of maxillary edentulous jaws. Using Mimics 17.0, Geomagic, and Unigraphics NX8.5 software, three-dimensional models were established: two mesial implants were placed vertically in the anterior region of the maxilla (bilateral central incisor, lateral incisor, and canine), and two distant implants were placed obliquely in the bilateral second premolar area at different inclined angles (15°, 30°, and 45°). The established models were designated I–IX. The models were subjected to dynamic load using Abaqus 6.12, with the working side posterior teeth loading of 150 N and simulation cycle of 0.875 s. Results. During the second to fourth phases of the mastication cycle, the stress was mainly concentrated on the neck of the distal implant. The stress of the distal implants was greater than that of mesial implants. Stress levels peaked in the third stage of the cycle. The stress of the distal cortical bone of distal implant of Model I reached the maximum of 183.437 MPa. The stress of the distal cortical bone and cancellous bone of distal implant of Model VIII represented the minima (62.989 MPa and 17.186 MPa, respectively). Conclusions. Our models showed optimal stress reductions when the mesial implants were located in the canine region and the distal implants tilted 30°.

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Purpose – The purpose of this paper is to present a new method about dynamic decision problems with three-parameter grey numbers from other angle of view which not only aggregates the attribute values of alternatives of all the periods, but also excavates changes of attribute values about alternatives between the adjacent periods. Design/methodology/approach – The authors adopt grey target method to calculate the distance between every alternative and the best, worst bull’s eye, the distance between change series and the best, worst change bull’s eye, then both distances can be aggregated to reflect information about two aspects. Findings – This dynamic decision-making method not only aggregates the existing state of alternatives all of the stages, but also excavates the change information from vertical and horizontal direction, the decision result conforming to decision maker’s psychological behavior is obtained though adjusting the priority parameter. Originality/value – The paper considers on change of alternative’s attribute values from one period to the next period, and the dynamic characteristic has been reflected adequately. The grey target decision-making method reflects the distance between alternative and bull’s eye, the comprehensive target distance between alternative and positive, worst bull’s eye about change series are separately provided. And the final target distance reflecting both existing state and change trend is constructed.