Towards a Generic Framework for the Performance Evaluation of Manufacturing Strategy: An Innovative Approach

Abstract

To be competitive in a manufacturing environment by providing optimal performance in terms of cost-effectiveness and swiftness of system changes, there is a need for flexible production systems based on a well-defined strategy. Companies are steadily looking for methodology to evaluate, improve and update the performance of manufacturing systems for processing operations. Implementation of an adequate strategy for these systems' flexibility requires a deep understanding of the intricate interactions between the machining process parameters and the manufacturing system's operational parameters. This paper proposes a framework/generic model for one of the most common metal cutting operations-the boring process of an engine block machining system. A system dynamics modelling approach is presented for modelling the structure of machining system parameters of the boring process, key performance parameters and their intrinsic relationships. The model is based on a case study performed in a company manufacturing engine blocks for heavy vehicles. The approach could allow for performance evaluation of an engine block manufacturing system condition. The presented model enables a basis for other similar processes and industries producing discrete parts.

A Systems Dynamics Enabled Real-Time Efficiency for Fuel Cell Data-Driven Remanufacturing

“…Thus, the SD approach allows the user to take into consideration information feedback which exists in the modeled system as well as describing the causal dependence of elements of the system which is being tested, [45]. Discrete Event Simulation, (DES), is the most popular approach for simulation of models, however due to its "unnecessary complexity" [46] and time consuming nature, it is not utilized in this research.…”

“…The SFD also helps enable the quantitative approach of solution in system dynamics, using three possible techniques: control theory, computational simulation and statistical analysis, [48]. Automotive manufacturing is extremely complex, requiring the machining, assembly and inspection of many components; hence formulating manufacturing within an automotive system using only mathematical equations is difficult [46]. A simulation approach, containing variables and relationships, which analyses and optimizes a given system structure is needed [46].…”

“…Automotive manufacturing is extremely complex, requiring the machining, assembly and inspection of many components; hence formulating manufacturing within an automotive system using only mathematical equations is difficult [46]. A simulation approach, containing variables and relationships, which analyses and optimizes a given system structure is needed [46]. Thus, within an automotive shop-floor, simulations using SD can help in understanding interactions and potential difficulties, allowing the evaluation of different alternatives, thus reducing the number of changes in the final system, [52].…”

“…In order to map out the structure of a complex system, a Causal Loop Diagram (CLD) is used as shown in Figure 6. In a complex system, [46], the cause effect connections often form loops which indicate information feedback between parameters. The structure and behaviour of this system is determined by the nature of these feedback loops.…”

“…These polarities represent the relationships between respective connected parameters. Adane & Nicolescu, (2018), [46] state that these polarities also indicate how a dependent parameter changes when an independent parameter changes. The notation B and R signify negative (or balancing) loop and positive (or reinforcing) loop respectively (these are feedback loops).…”