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PLM optimization with cooperation of PMS in production stage

Paavel M., Snatkin A., Karjust K.

Archives of Materials Science and Engineering

2013

Vol. 60, nr 1

38--45

Purpose: To present a short overview of PLM and its directions including evolution, different phases of PLM and Closed-loop PLM. To describe a new approach in order to improve the closed-loop lifecycle by using production monitoring systems at an early stage of the lifecycle. Monitoring of products in their early life stages in production processes and to use this information for the improvement of the product development and implementation process. Design/methodology/approach: Implementation of a production monitoring system plays an important role in our approach. Sensors that are part of a production monitoring system are sending valuable data from the production to the PLM database where it can be used for production development and analysis. Findings: It is demonstrated that installation of the production monitoring system improved product lifecycle at the beginning of their lifecycle. Feedback from production monitoring systems helps to make better conclusions and quicker decisions in the development phase and gives real-time input to the analysis process. Research limitations/implications: Production monitoring systems improve product lifecycle management in the early stages but do not support the product directly in the other life stages. Decisions can be made only based on this information. Practical implications: Information gathered by production monitoring systems could help to modify the production development and implementation process . Also afterwards the information can be used to identify deviations and mistakes. All this is necessary to fill the gaps in product lifecycle. Originality/value: The proposed installation of production monitoring systems improves new data income to the system that provides better decision making opportunities. Based on this real-time information, it is easier to make changes in the product development phases.

Development of integrated product model for supporting production monitoring system on an automobile assembly industry

Raharno S., Martawirya Y. Y.

Journal of KONES

2011

Vol. 18, No. 3

367-374

Making a good production planning is a first step to produce products in effective and efficient ways. A good production planning needs information about the real conditions in the shop-floor. Without knowing the actual conditions in the shop-floor, it will be difficult to plan production well. In order to know the conditions of the shop-floor, a production monitoring system is needed. This paper deals with development of integrated product model for supporting production monitoring system on an automobile assembly industry. The integration of information between the production controls with the shop-floor is needed to build a production monitoring system. One way to integrate the two systems is by using a product model that is a representation of a real product. In general, the research method used in this research is the development of product models and other related models. The modelling concept used in this research is object oriented modelling. After that, this research also has developed a database in accordance with the developed models and interfaces used to manipulate them. The main proposed models in this research are the product type model and the product model. The product type model is the product model that represents the product designs. On the other hand, the product model is a model that represents the actual products. If the data on the product type model is relatively static, then the data on the product model is dynamic depending on the state of the real product. Each product model will have production sequence processes in accordance with the sequence processes of the represented product. Each time a process of real product is finished, and then the related process model in the product model will be updated. The condition of the processes that has occurred in the shop-floor will be known by manipulating data of the product models.