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Mathematical modeling to standardize times in assembly processes: Application to four case studies

Abstract:

Purpose: This paper proposes model-based standard times estimates using multiple linear regression, non-linear optimization, and fuzzy systems in four real cases of assembly lines. The work includes a description of the models and compares their performance with measurements obtained through the conventional chronometer method. These models allow estimating standard times without reconducting field studies. Design/methodology/approach: For the development of the time study, the methodology proposed by the International Labour Organization (ILO) was used as a baseline, which is structured in three phases: the selection of the case study, the registration of the process by direct observation, and the calculation/estimation of the standard time. The selected case studies belong to real assembly lines of motorcycles, television sets, printed circuit boards (PCB), and bicycles. Findings: In the motorcycle’s assembly case, the study allowed the construction of fourteen linear regression models: seven to estimate standard times for assembling the front parts and seven for the rear of the different motorcycle types. Compared to the conventional chronometer method, the results never exceeded 10% of the measured values. Regarding the cases of assembling TV sets and PCBs, the study considered the construction of nonlinear optimization models that allow making appropriate pbkp_redictions of the standard times in their assembly lines. Finally, for the bicycle assembly line, a fuzzy logic model was constructed and validated to represent the standard time. Research limitations/implications: To ensure the confidentiality of the companies used in the case study: all the names of the companies, services and the models of manufactured products are omitted. Originality/value: The literature consulted does not refer to the representation of standard time on assembly lines using mathematical models. The construction of these models with empirical data from real-assembly lines was a valuable aid to the companies involved in supporting activity planning.