# A System Dynamics Approach to Optimize Milk Production in an Industrial Ranch
## 2 Literature Review  
A this research aimed to maximize milk production at the Ahrar Sepahan ranch using a dynamic system approach, the literature review was divided into two parts. In the first part, since animal production systems are generally complicated and management decision-making problems are often developed in light of this complexity [12], we focused on research efforts geared toward understanding the milk production process. In the second part, we considered scenario definitions in the form of the system dynamics model. These scenarios were defined after the identification of sensitive variables and their optimization through the DOE technique. DOE is among the statistical methods for determining key variables affecting the qualitative specification in question. Based on his studies in the 1950s and 1960s, [PERSON] authenticated the DOE. Statistical design for empirical experiments is a principle in laboratory and industrial research. These designs lead to more reliable results, saving time, and significantly reducing the number of experiments, ultimately leading to process optimization. The DOE is a useful method by which the data are analyzed for objective validity and deduction before the experiments. By performing pilot studies and experimental plans, one can determine the optimal value of the measurement results (responses) or the conditions in which the conflicting responses have proper adaptation. An important issue in industrial ranching is coping with different diseases in order to increase the production and milk quality. The first goal of animal health economics is to provide knowledge of the costs related to different livestock diseases and the second goal is to support decision-making on the most cost-efficient techniques to reduce these diseases [9]. One critical disease is the mastitis disorder in dairy cows, which is related to the rate of milk production [9; 15]. The study reported by [PERSON] et al. [7] recognizes metabolic/digestive disorder, mastitis/udder problems, and calving problems as the major causes of livestock death. In addition to disease, determination of the age at first calving (AFC), which indicates the growth rate of heifers, is considered as one of the main parameters in herd health programs. The suitable development of replacement heifers as an important calving program and the continuation of the production process in the herd was considered by [PERSON] et al. [16]. Proper management techniques improve the milk production status. Research carried out by [PERSON] et al. [17] recommends that in order to maximize productivity in the U.S. milk production industry, it is necessary to use technologies with an integrated systematic approach on one hand, and implement a proper technique considering the size of the farm on the other hand. One of these technologies is the automatic milking system (AMS), which is used regarding the conditions and environment. For example, [PERSON] et al. [2] divided 529 dairy farms in North America into six categories in terms of using an automatic milking system and proposed some recommendations for each category to increase productivity. [PERSON] et al. [18] proposed the use of sensor systems that led to the improved management of different health care activities as well as production in lactating cattle. These systems could measure the physiological, behavioral, and production indicators of each cow. In research carried out on Kentucky Holstein herds, the respondents recognized four management techniques as factors influencing the improvement of milk production including attention to detail, nutrition, cow comfort, and nutrition quality [19]. The majority of animal husbandry studies (a branch of science dealing with farming, breeding and care of farm animals) including laboratory, hygiene, and management studies consider livestock population as an important factor. The dynamics of livestock population are critical to understanding the characteristics and developing the capacity of production systems [7; 12].