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At the current time, textile product quality is the most attractive factor for the consumer market. Iraqis’ textile yarn industries are facing a lot of difficulties and competition of cotton yarn products, which has been increased versus artificial fibers. The main problems include the physical and chemical characteristics of cotton yarn because of genetic, environmental, harvesting, and ginning factors. The Statistical control process is a powerful and useful methodology used to solve problems in textile yarn industries to achieve process stability, improve process capability, and reduce process variability. The main objective of this study is to apply control charts and comparison control chart performance of yarn spinning data for quick detection of process shifts that occur to take corrective action. Therefore, in this study, the control charts have been applied at the Wasit state company for textile industries to control the quality of cotton yarns produced. Applying control charts in all yarn spinning stages is a very important issue, especially in production cost and yarn quality. Quality control charts selected for variables that include ( X ¯ -R and X ¯ -S charts) are constructed to describe tenacity, elongation, and the coefficient of variation. Thirty samples size of yarns with five reading of observations per sample of count 1/27Ne are drawn from spinning machine. Minitab is statistical software used to construct the control charts because of its good reputation which is confirmed by the results achieved in our research. The final results of this study will help us to distinguish yarns parameters in the points of the economy and the quality, by comparison, their above-mention parameters.

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Scheduling models for groups of parts have become more widely used in the industrial companies because of intensification of competition among them to get optimization in the delivery orders, reduce costs and increase quality. "Production scheduling is a meaning of verify a best or close to best achievement time plan for performing job, Production scheduling linked with the group technology applications is called Group Scheduling (GS). The objective of this research is to find optimum sequence of parts through cell formation and group scheduling. In this research, a lower bound for best possible Makespan is calculated by branch and bound algorithm and the best order of groups and parts generated. In this research, Branch and Bound algorithm was developed by the researcher to generate machine cell and part family then gathering groups to find sequence of groups as well as parts within it and calculate Makespan for problem". The developed algorithm have been tested by case study consist of four products processed on nine machine, the results from examining and testing of the developed algorithm is three machine cell and part family (MC-1,MC-2 and MC-3) as well as optimal Makespan for MCs is(344,152,122).

Manufacturing industries are rapidly changing from production of scale to production of scope characterized by short product life cycles and increased product varieties. This implies a need to improve the efficiency of job shops while still maintaining their flexibility. These objectives are achieved by Flexible manufacturing systems (FMS). The basic aim of FMS is to bring together the productivity of flow lines and the flexibility of job shops, this duality of objectives makes the management of FMS complex. In this research, the loading problem in FMS, which is viewed as selecting a subset of jobs from the job pool and allocating them among available machines, is considered. The research investigates the number of machine loading approaches, which aim to meet the delivery dates of production orders, and at the same time reduce the manufacturing cost.