Mathematical models for the formation and evaluation of manufacturing cells in a textile company: A case study

Purpose: Use mathematical models of Mixed Integer Linear Programming oriented to cellular distribution and aggregate production planning in order to obtain the appropriate product family for each manufacturing cell and from this, minimize production and material handling costs through the allocation of production resources. Design/methodology/approach: This article develops two mathematical models in LINGO 18.0 software, performing the computational calculation to obtain the best efficiency in cell formation at minimum production cost. Findings: The mathematical model oriented to the formation of manufacturing cells allows a grouping of products and machines with 82.5% group efficiency. By reallocating machines to each cell and redistributing facilities, the cost of material handling is reduced by 35.1%, and the distance traveled in product manufacturing is reduced by 26.6%. The mathematical model of aggregated planning provides information on production resource requirements such as personnel, machinery, distances traveled, as well as the cost generated by the need to outsource part of the production, inventory maintenance and overtime work. Research limitations/implications: It is necessary to clearly define the capacity variables. The model does not take into account the cost of mobilizing machines and readjusting facilities. Practical implications: The case study company can adequately plan production and efficiently manage its resources. Social implications: The study can be applied to other textile SMEs. Originality/value: The aggregate production planning model requires the assignment of the mathematical model of manufacturing cell formation in order to calculate the resource requirements needed to meet a demand

Geometric Modeling of Cellular Materials for Additive Manufacturing in Biomedical Field: A Review

Advances in additive manufacturing technologies facilitate the fabrication of cellular materials that have tailored functional characteristics. The application of solid freeform fabrication techniques is especially exploited in designing scaffolds for tissue engineering. In this review, firstly, a classification of cellular materials from a geometric point of view is proposed; then, the main approaches on geometric modeling of cellular materials are discussed. Finally, an investigation on porous scaffolds fabricated by additive manufacturing technologies is pointed out. Perspectives in geometric modeling of scaffolds for tissue engineering are also proposed

A Taguchi method application for the part routing selection in Generalized Group Technology: A case Study

Cellular manufacturing (CM) is an important application of group technology (GT) that can be used to enhance both flexibility and efficiency in today’s small-to-medium lot production environment. The crucial step in the design of a CM system is the cell formation (CF) problem which involves grouping parts into families and machines into cells. The CF problem are increasingly complicated if parts are assigned with alternative routings (known as generalized Group Technology problem). In most of the previous works, the route selection problem and CF problem were formulated in a single model which is not practical for solving large-scale problems. We suggest that better solution could be obtained by formulating and solving them separately in two different problems. The aim of this case study is to apply Taguchi method for the route selection problem as an optimization technique to get back to the simple CF problem which can be solved by any of the numerous CF procedures. In addition the main effect of each part and analysis of variance (ANOVA) are introduced as a sensitivity analysis aspect that is completely ignored in previous research.Cellular Manufacturing; generalized Group Technology; route selection problem; Taguchi method; ANOVA; sensitivity analysis

Growth behavior of human adipose tissue-derived stromal/stem cells at small scale : numerical and experimental investigations

Human adipose tissue-derived stromal/stem cells (hASCs) are a valuable source of cells for clinical applications, especially in the field of regenerative medicine. Therefore, it comes as no surprise that the interest in hASCs has greatly increased over the last decade. However, in order to use hASCs in clinically relevant numbers, in vitro expansion is required. Single-use stirred bioreactors in combination with microcarriers (MCs) have shown themselves to be suitable systems for this task. However, hASCs tend to be less robust, and thus, more shear sensitive than conventional production cell lines for therapeutic antibodies and vaccines (e.g., Chinese Hamster Ovary cells CHO, Baby Hamster Kidney cells BHK), for which these bioreactors were originally designed. Hence, the goal of this study was to investigate the influence of different shear stress levels on the growth of humane telomerase reversed transcriptase immortalized hASCs (hTERT-ASC) and aggregate formation in stirred single-use systems at the mL scale: the 125 mL (= SP100) and the 500 mL (= SP300) disposable Corning® spinner flask. Computational fluid dynamics (CFD) simulations based on an Euler⁻Euler and Euler⁻Lagrange approach were performed to predict the hydrodynamic stresses (0.06⁻0.87 Pa), the residence times (0.4⁻7.3 s), and the circulation times (1.6⁻16.6 s) of the MCs in different shear zones for different impeller speeds and the suspension criteria (Ns1u, Ns1). The numerical findings were linked to experimental data from cultivations studies to develop, for the first time, an unstructured, segregated mathematical growth model for hTERT-ASCs. While the 125 mL spinner flask with 100 mL working volume (SP100) provided up to 1.68.10⁵ hTERT-ASC/cm² (= 0.63 × 10⁶ living hTERT-ASCs/mL, EF 56) within eight days, the peak living cell density of the 500 mL spinner flask with 300 mL working volume (SP300) was 2.46 × 10⁵ hTERT-ASC/cm² (= 0.88 × 10⁶ hTERT-ASCs/mL, EF 81) and was achieved on day eight. Optimal cultivation conditions were found for Ns1u < N < Ns1, which corresponded to specific power inputs of 0.3⁻1.1 W/m³. The established growth model delivered reliable predictions for cell growth on the MCs with an accuracy of 76⁻96% for both investigated spinner flask types