چارچوب تجزیه و تحلیل یکپارچه برای بهبود فرایند تولید در سیستم نرم افزار فشرده

Software-intensive systems involve the using of software engineering that cooperate with other engineering fields to achieve common goals, e.g., to provide good quality products to the customers in the right time. In the production automation systems as examples of software-intensive systems, the projects managers want to observe the production processes, so they can check the conformance between the running systems and the planned systems, e.g., whether the systems provide the expected products in the right time, how much time needed to finish a sequence of jobs is. However, the observation of production processes in these systems is difficult because heterogeneous data models are used to represent data from business and production layers. We propose an integrated analysis framework for improving production process in the production automation systems. Current results show that the framework can help the project manager to plan and conduct production process data collection and analysis for improving the process quality.

Software - intensive systems typically involve software e n gineering that support and cooperate with other engineering fields, e.g., mechanical engi neering or electrical engineering, to achieve common goals, e.g., to provide g ood quality products to the customers in the right time. Production automation systems as example of software - intensive systems, are commonly used for producing manuf act ure products in mass production, fast finishing - time, an d often changed configurations due to changes in customer orders. Our research is dealing with production process manageme nt in the production automation systems, especially in observing and analyzing production process data for supporting the project managers’ decisions on enhancing quality of the process and the products. In the production automation systems, the project managers observe and measure the quality of the running processes against the desi gned processes, to be able to take further decisions on improving the quality of processes and products, e.g., to change the configuration of layout due to users’ requirements, to add more machines to th e layout to finish the products faster. However, the production process observation is difficult due to heterogeneity of tools and data models used by stakeholders from different engineering fields or laye rs. The manual process data collection from different engineering tools is error - prone and takes a lot of time, while the project managers’ decisions are based on their ex periences and expertise rather than based on the real process data. Hence, the systems are depending on the availability of the experts, which is scarce and limited. To solve these problems, we propose to have an integrated analysis framework for production process data collection and analysis from the production automation sy stems. The current results show that the integrated analysis framework can support a more accurate project manager decision making. Also the using of automated approach for data collection and analysis make the work more efficient than by using the manual approach