Browsing by Subject "Produktion"

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Application of nature-inspired optimization algorithms to improve the production efficiency of small and medium-sized bakeries
(2023) Babor, Md Majharul Islam; Hitzmann, Bernd
Increasing production efficiency through schedule optimization is one of the most influential topics in operations research that contributes to decision-making process. It is the concept of allocating tasks among available resources within the constraints of any manufacturing facility in order to minimize costs. It is carried out by a model that resembles real-world task distribution with variables and relevant constraints in order to complete a planned production. In addition to a model, an optimizer is required to assist in evaluating and improving the task allocation procedure in order to maximize overall production efficiency. The entire procedure is usually carried out on a computer, where these two distinct segments combine to form a solution framework for production planning and support decision-making in various manufacturing industries. Small and medium-sized bakeries lack access to cutting-edge tools, and most of their production schedules are based on personal experience. This makes a significant difference in production costs when compared to the large bakeries, as evidenced by their market dominance. In this study, a hybrid no-wait flow shop model is proposed to produce a production schedule based on actual data, featuring the constraints of the production environment in small and medium-sized bakeries. Several single-objective and multi-objective nature-inspired optimization algorithms were implemented to find efficient production schedules. While makespan is the most widely used quality criterion of production efficiency because it dominates production costs, high oven idle time in bakeries also wastes energy. Combining these quality criteria allows for additional cost reduction due to energy savings as well as shorter production time. Therefore, to obtain the efficient production plan, makespan and oven idle time were included in the objectives of optimization. To find the optimal production planning for an existing production line, particle swarm optimization, simulated annealing, and the Nawaz-Enscore-Ham algorithms were used. The weighting factor method was used to combine two objectives into a single objective. The classical optimization algorithms were found to be good enough at finding optimal schedules in a reasonable amount of time, reducing makespan by 29 % and oven idle time by 8 % of one of the analyzed production datasets. Nonetheless, the algorithms convergence was found to be poor, with a lower probability of obtaining the best or nearly the best result. In contrast, a modified particle swarm optimization (MPSO) proposed in this study demonstrated significant improvement in convergence with a higher probability of obtaining better results. To obtain trade-offs between two objectives, state-of-the-art multi-objective optimization algorithms, non-dominated sorting genetic algorithm (NSGA-II), strength Pareto evolutionary algorithm, generalized differential evolution, improved multi-objective particle swarm optimization (OMOPSO) and speed-constrained multi-objective particle swarm optimization (SMPSO) were implemented. Optimization algorithms provided efficient production planning with up to a 12 % reduction in makespan and a 26 % reduction in oven idle time based on data from different production days. The performance comparison revealed a significant difference between these multi-objective optimization algorithms, with NSGA-II performing best and OMOPSO and SMPSO performing worst. Proofing is a key processing stage that contributes to the quality of the final product by developing flavor and fluffiness texture in bread. However, the duration of proofing is uncertain due to the complex interaction of multiple parameters: yeast condition, temperature in the proofing chamber, and chemical composition of flour. Due to the uncertainty of proofing time, a production plan optimized with the shortest makespan can be significantly inefficient. The computational results show that the schedules with the shortest and nearly shortest makespan have a significant (up to 18 %) increase in makespan due to proofing time deviation from expected duration. In this thesis, a method for developing resilient production planning that takes into account uncertain proofing time is proposed, so that even if the deviation in proofing time is extreme, the fluctuation in makespan is minimal. The experimental results with a production dataset revealed a proactive production plan, with only 5 minutes longer than the shortest makespan, but only 21 min fluctuating in makespan due to varying the proofing time from -10 % to +10 % of actual proofing time. This study proposed a common framework for small and medium-sized bakeries to improve their production efficiency in three steps: collecting production data, simulating production planning with the hybrid no-wait flow shop model, and running the optimization algorithm. The study suggests to use MPSO for solving single objective optimization problem and NSGA-II for multi-objective optimization problem. Based on real bakery production data, the results revealed that existing plans were significantly inefficient and could be optimized in a reasonable computational time using a robust optimization algorithm. Implementing such a framework in small and medium-sized bakery manufacturing operations could help to achieve an efficient and resilient production system.
Food-grade Lactobacilli expression systems for recombinant enzymes
(2013) Böhmer, Nico; Fischer, Lutz
Lactobacilli are Gram-positive bacteria used throughout the food industry as traditional starters for various fermented foods. Lactobacilli would be superior for recombinant enzyme production regarding the food safety demands since most of them are Generally Recognised As Safe (GRAS) organisms. The major advantages of Lactobacilli as food-associated microorganisms used for recombinant enzyme production are their safe and sustainable use as overall safety food-grade expression systems. In the work presented, Lactobacilli were studied in detail as food-grade expression systems for recombinant enzyme production. In a first analysis, the two pSIP expression systems, pSIP403 and pSIP409, were investigated to produce a hyper-thermophilic Beta-glycosidase (CelB) from Pyrococcus furiosus in Lactobacillus plantarum NC8 and Lactobacillus casei as hosts, respectively. Both Lactobacilli harbouring the pSIP409-celB vector produced active CelB in batch bioreactor cultivations, while the specific CelB activity of the cell-free extract was about 44% higher with Lb. plantarum (1,590 ± 90 nkatpNPGal/mgprotein) than with Lb. casei (1,070 ± 66 nkatpNPGal/mgprotein). A fed-batch bioreactor cultivation of Lb. plantarum NC8 pSIP409-celB resulted in a specific CelB activity of 2,500 ± 120 nkatpNPGal/mgprotein. A basal whey medium with supplements was developed as an alternative to the cost intensive MRS medium used. About 556 ± 29 nkat pNPGal/mgprotein of CelB activity was achieved in bioreactor cultivations using this medium. It was shown that both Lactobacilli were potential expression hosts for recombinant enzyme production. An additional approach was performed to produce a metagenome-beta-galactosidase using Lb. plantarum NC8 with the pSIP expression system. Using this system, a quite low maximal galactosidase activity of only 0.18 nkatoNPGal/mgprotein was detected. A 13 times higher activity of 2.42 nkatoNPGal/mgprotein was produced after the knock out of the interfering native Kluyveromyces lactis Beta-galactosidase in the well-known food-grade K. lactis pKLAC2 expression system. Nevertheless, the best performing expression system for the recombinant production of the metagenome-derived enzyme was the Escherichia coli BL21 strain with a pET vector, resulting in the highest Beta-galactosidase of 82.01 nkatoNPGal/mgprotein. Beside the use of the pSIP expression system, a novel expression system for Lb. plantarum was developed. This system is based on the manganese starvation-inducible promoter from the specific manganese transporter of Lb. plantarum NC8 which was cloned for the first time. The expression of CelB was achieved by cultivating Lb. plantarum NC8 at low manganese concentrations with MRS medium and the pmntH2-celB expression vector. A CelB activity of 8.52 µkatoNPGal/L was produced in a bioreactor. The advantages of the novel expression system are that no addition of an external inducing agent was required, and additionally, no further introduction of regulatory genes was necessary. The new promoter meets the general demands of food-grade expression systems. The glutamic acid racemase of Lb. plantarum NC8 was cloned and characterized in this work for the first time as a possible target for a food-grade selection system for this species. Glutamic acid racemases (MurI, E.C. 5.1.1.3) catalyse the racemisation of L- and D-glutamic acid. MurIs are essential enzymes for bacterial cell wall synthesis, which requires D-glutamic acid as an indispensable building block. Therefore, these enzymes are suitable targets for antimicrobial drugs as well as for the potential design of auxotrophic selection markers. A high expression system in E. coli BL21 was constructed to produce and characterize the biochemical properties of the MurI from Lb. plantarum NC8. The recombinant, tag-free Murl was purified by an innovative affinity chromatography method using L-glutamic acid as the relevant docking group, followed by an anion exchange chromatography step (purification factor 9.2, yield 11%). This two-step purification strategy resulted in a Murl sample with a specific activity of 34.06 µkatD-Glu/mgprotein, comprising a single protein band in SDS-PAGE. The purified Murl was used for biochemical characterization to gain in-depth knowledge about this enzyme. Only D- and L-glutamic acid were recognised as substrates for the Murl with similar kcat/Km ratios of 3.6 sec-1/mM for each enantiomer. The findings in this study may contribute to further development and implementation of food-grade Lactobacilli expression systems for recombinant enzyme production. Furthermore, the results obtained may help to optimise and select hosts and expression systems for industrial enzyme production for the needs of the food industry.