Optimization model for production scheduling taking into account preventive maintenance in an uncertainty-based production system

In the dynamic yet uncertain environment of Industry 4.0, industrial companies are utilizing the benefits of contemporary technologies in manufacturing by striving to implement optimization models in each stage of the decision-making process. Many organizations are focusing particularly on the optimization of two key aspects of the manufacturing process - production schedules and maintenance plans. This article presents a mathematical model with the main advantage of finding a valid production schedule (if such exists) for the distribution of individual production orders on the available production lines over a specified period. The model further considers the scheduled preventive maintenance activities on the production lines, as well as the preferences of the production planners regarding the start of the production orders and non-use of certain machines. When necessary, it also offers the possibility to make timely changes in the production schedule, and thus to handle the uncertainty as precisely as possible. For the verification of the model, two experiments were conducted (quasi-real and real-life), with data from a discrete automotive manufacturer of locking systems. The results from the sensitivity analysis demonstrated that the model further optimizes the execution times of all orders, and specifically the production lines usage - their optimal load and non-use of unnecessary machines (valid plan with 4 out of 12 lines not used). This allows for cost savings and raises the overall efficiency of the production process. Thus, the model adds value for the organization by presenting a production plan with optimal machine usage and product allocation. If incorporated into an ERP system, it could distinctly save time and streamline the production scheduling process

n-3 polyunsaturated fatty acids provoke a specific transcriptional profile in rabbit adipose-derived stem cells in vitro

Adipose-derived stem cells (ADSCs) possess multipotent properties, and their proper functionality is essential for further development of metabolic disorders. In the current study, we explored the impact of two n-3 LC-PUFAs (long-chain polyunsaturated fatty acids, DHA-docosahexaenoic; C22:6, and EPA-eicosapentaenoic; C20:5) on a specific profile of lipolytic-related gene expressions in the in vitro-differentiated subcutaneous and visceral ADSCs from rabbits. The subcutaneous and visceral ADSCs were obtained from 28-day-old New Zealand rabbits. The primary cells were cultured up to passage 4 and were induced for adipogenic differentiation. Thereafter, the differentiated cells were treated with 100 µg EPA or DHA for 48 hr. The total mRNA was isolated and target genes expression evaluated by real-time RCR. The results demonstrated that treatment of rabbit ADSCs with n-3 PUFAs significantly enhanced mRNA expression of Perilipin A, while the upregulation of leptin and Rab18 genes was seen mainly in ADSCs from visceral adipose tissue. Moreover, the EPA significantly enhanced PEDF (Pigment Derived Epithelium Factor) mRNA expression only in visceral cells. Collectively, the results suggest activation of an additional lipolysis pathway most evident in visceral cells. The data obtained in our study indicate that in vitro EPA up-regulates the mRNA expression of the studied lipolysis-associated genes stronger than DHA mainly in visceral rabbit ADSCs. Eкaterina Vackova1| Darko Bosnakovski2| Bodil Bjørndal3| Penka Yonkova4|Natalia Grigorova1| Zhenya Ivanova1| Georgi Penchev4| Galina Simeonova5|Lyuba Miteva6| Anelya Milanova1| Tatyana Vachkova7| Spaska Stanilova6|Ivan Penchev Georgie

Effects of castration-induced visceral obesity and antioxidant treatment on lipid profile and insulin sensitivity in New Zealand white rabbits

Molecular mechanisms, responsible for the impaired insulin-sensitivity state due to the obesity are not fully understood in both humans and animals. The purpose of this study was to i