Globalization, advanced technology, and increased sophisticated customer demands change the way of conducting business. Old business models no longer work in new economy. Defects rate of product plays an important role for the improvement of yield and financial conditions of any company. The objectives of this paper are to study and evaluate processes of the case organization, to find out current sigma level and finally to improve existing sigma level through productivity improvement. According to the objectives, current sigma level has been calculated and given suggestions for improvement. This has been done by using six-sigma DMAIC cycle. Especially in improve phase of DMAIC cycle, different improvement tools are used like 5s, supermarket and line balancing etc. By using these it has been possible to improve productivity by reducing defect rate. This research work has been carried out in a fan manufacturing company to show how to improve its productivity and quality by using Six-sigma. This paper related to work is not only applied to fan manufacturing company but also in any other types of organizations. By implementing Six-sigma a perfect synchronization among cost, quality, production time and control time will be observed.

Productivity Improvement by using Six-Sigma

Applying lean in aerospace manufacturing

https://pureadmin.qub.ac.uk/ws/files/137125464/2017_Cycle_time_study_of_wing_spar_assembly_on_aircraft_factory.pdf

Cycle time study of wing spar assembly on aircraft factory

Lean Manufacturing That Works

The uncertainty of mechanical assembly process usually brings great challenge to product quality control and assurance. The systematic approach should be employed in the research to find a comprehensive solution. The quality assurance model for assembly (QAMA), based on the analysis of the major problems in the mechanical assembly process and the factors that affect the quality of products, is established by means of three working models: the assembly process model (APM), the activity control model (ACM), and the quality data model (QDM). The APM formulates the assembly process starting with the analysis of process flow, logical scheme, and key factors. The ACM is built by defining the attributes of control activity, mapping relationship between the control activities and its objects in the multiview space and layers. The ACM presents the control flow with the logical relations among control activities as well as the control rules. Based on the two models mentioned above, the QDM supports the acquisition of quality data through data-collecting carriers along assembly process and defines the data structure to support the system model. All of the three models are grouped into a framework which integrates the technical approaches and solutions for quality assurance in mechanical assembly. Based on modeling studies, a computer-integrated and internet-based system called quality assurance system in mechanical assembly (QAS/MA) has been developed. And the development of QAS/MA proves that APM, ACM, QDM, and QAMA are practical and feasible.

Quality assurance model in mechanical assembly

Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Industrial & Manufacturing Engineering

/pdf/lean-six-sigma-applications-in-aircraft-assembly-40alg9tgzn.pdf

Siddhartan Ramamoorthy

Papers

Lean Six-Sigma applications in aircraft assembly