Understanding the Requirements of Forecast in Demand Driven Material Requirements Planning
Examensarbete för masterexamen
Quality and operations management (MPQOM), MSc
In a world with high variations and uncertainties, the traditional material requirement planning is no longer sufficient. This planning system relies on fixed schedules and do not consider deviations. Therefore, a new demand driven material requirement planning (DDMRP) methodology has been introduced. This method enables companies to control variability using buffer levels to achieve high service level and low inventory costs. That said, companies are currently facing numbers of internal and external challenges when using this new method. The challenges are divided into four areas; external supply chain transparency, internal forecast methods, demand and production planning as well as setup of the DDMRP system. Hence, the purpose of this study is to investigate what is required externally from the supply chain and internally in the organization in order to use the DDMRP method for generating orders towards production and suppliers. Further, the study also aims to investigate the potential ways to incorporate forecast in sizing the DDMRP buffers. One company that has met these challenges is AeroCo, which is currently in an implementation phase of DDMRP. Semi-structured interviews with 23 company representatives from various department, along with historical demand, production and delivery data, have been the foundation of the data collection. The qualitative data was gathered and analyzed using influences from a systematic approach presented by Gioia, Corley, and Hamilton. The quantitative data was compiled in excel and compared to find the best forecast method. Moreover, the literature review was used to obtain a better understanding of supply chain transparency, different forecast methods, overall demand and production planning, as well as the DDMRP method. Altogether, the theoretical framework combined with the empirical findings led to conclusions concerning the research questions. Firstly, it can be concluded that DDMRP goes hand in hand with reaching full supply chain integration and the implementation of collaborative planning, forecasting, and replenishment. Secondly, it has been shown that relying only on the qualitative or quantitative forecast is not sufficient. For this reason, an integration method with both qualitative and quantitative approaches should be included. Thirdly, regarding the internal demand and product planning processes, it can be noted that the sales and operations planning process does not have to go through major changes in order to use the DDMRP method. However, the master production scheduling process will need to be further adjusted. Lastly, when incorporating the forecast into DDMRP, quality errors do not need to be incorporated since it is handled by a variability factor. Instead, the forecast used for DDMRP should reflect the general forecast but include a demand adjustment factor in order to take vacations and other capacity constraints into consideration.
Produktion , Transport , Grundläggande vetenskaper , Hållbar utveckling , Övrig industriell teknik och ekonomi , Production , Transport , Basic Sciences , Sustainable Development , Other industrial engineering and economics