Modelling Decision-Making Processes in the Management Support of the Manufacturing Element in the Logistic Supply Chain

Abstract

This paper highlights the problems of mathematical modelling for a specific element of the logistic supply chain, that is, the manufacturing system. The complex manufacturing system consisting of a determined number of parallel subsystems is modelled. The fact that the same manufacturing procedure can be carried out in various locations is emphasised. Control algorithms as well as manufacturing strategies are explained. The equations of state are introduced. The two-stage criterion lets us use the result data generated by the simulator of the production system as the initial data for further processing; however, the main goal remains to minimise the time of the course of production. The precisely elaborated case study implements initial data obtained by preceding simulation procedures carried out in manufacturing systems consisting of three, four, and five subsystems.

Cooperation Modes of Operations and Financing in a Low-Carbon Supply Chain

“…Lozano et al [27] showed that, under different cooperation levels, enterprises will work accordingly in order to reduce costs. Bucki and Suchánek [28] focused on the design and optimization of logistics and production. Ma and Lou [29] investigated the complex characteristics caused by the price competition in multichannel household appliance supply chains.…”

Combined Use of Mathematical Optimization and Design of Experiments for the Maximization of Profit in a Four‐Echelon Supply Chain

“…The cost of the interest rate (CTP) is integrated into the model in (8) showing the total financing cost in the supply chain, based on the costs of the manufacturer (CPR ) and the distribution center (CPF ). Equation (9) shows the calculation for each echelon by means of multiplication only resulting from the difference of the real prices (− ) and target price (TR mr ) of the materials or products according to the case of the echelon that exceeds the target price for which the difference of the real price in relation to the target price will be calculated, and this difference will be multiplied by the amount sent (QR ) and by the assigned interest rate.…”

“…For example, an increase in supply chain capacity may reduce delivery times, while implying an economic cost, and at the same time, it may yield and increment in the complexity of the network design problem, by a combinatorial increment in the number of feasible solutions. In the case of supply chains, even manufacturing systems can be considered interrelated [8], generating very large and complex systems. Improvements in quality and delivery times require an economic investment, while low quality levels may entail the need to resort to external suppliers.…”

Coping with Complexity When Predicting Surface Roughness in Milling Processes: Hybrid Incremental Model with Optimal Parametrization

“…Additionally, the number of proposed random perturbations at each temperature is 100 and the number of accepted solutions to proposed random perturbations is 30. The exploration space is ∈ [1,10], ∈ [1,10], ∈ [1,3] where , ∈ Z and ∈ R.…”

“…Despite the progress in science and technology, manufacturing processes are still considered complex systems consisting of several interacting subsystems with noisy, timevariant, and nonlinear behavior [1,2]. New models are then required to better deal with manufacturing companies' threats innovating in whole value chain [3].…”