Introducing the EPP house (topological space) method to solve MRP problems

Abstract

The problem of product and process planning analysed so far is how we can take advantage of our strategy in planning. Among the principles of manufacturing and service management concepts is that after planning demand, planning transformation is one of the key steps of integrated efficiency; it makes it possible to save costs that are not value adding and are not necessary from the customer’s point of view. Currently, the methods of material requirements and capacity planning can be seen as classic solutions that are based on dependency relations between different resources, which can be dynamic in space and time. Measuring and recording capacities raise several problems in addition to the fact that our planning methods are not always satisfying. In the literature, the methods of material requirements planning or manufacturing resource planning (MRP) are not typically optimization methods, so they do not guarantee the best solution, and even if our planning methods were satisfying, several manufacturing restrictions (the time allowed, the complexity of the planning process, the lack of testing opportunities, etc.) could prevent us from reaching satisfying application. It is necessary to create a simple planning algorithm that can give the planner a greater degree of freedom and that would be simple and algorithmic in order to maintain continuous conscious control, putting an end to planning uncertainty and leading us to the best solution under the given conditions. The aim of our research is to introduce a novel, simple planning algorithm, similar to heuristic methods that eliminates the problem of defining the order quantity when applying traditional methods, which prevents us from determining in advance which method is desirable (causing unnecessary planning steps); computer-based solutions hide the causal relations of the methodology from the planner (causing unreliability uncertainty).

Understanding and acceptance of systems engineering in automotive product development

“…(Vanek et al, 2017) Despite the facts that automotive industry has been facing with an immense technical revolution as well as new organizational challenges arise aiming to better meet the stakeholder needs, firms have barely applied this methodology so far. Although, an amount of studies concern imagined or realized effects of SE within the field, they mostly touch production cases or discuss the implementation on a theoretical basis (Dumitrescu et al, 2013;Gál et al, 2013;Fischer et al, 2020;Gyenge et al, 2021;Rabe et al, 2022). Even though the unequivocal benefit of SE appears in other industrial sectors including development activities, little evidence has been published on its utilization in APD (Henderson & Salado, 2021).…”