TY - JOUR

T1 - Lateness in production systems - In a nutshell

T2 - How to determine the causes of lateness at work systems?

AU - Mütze, Alexander

AU - Hiller, Tobias

AU - Nyhuis, Peter

N1 - Funding Information: This project is funded by the German Federal Ministry of Education and Research , as part of the Aviation Research and Technology Program of the Lower Saxony Ministry of Economics, Labor, Transport and Digitalization (funding code ZW 1-80157862 ).

PY - 2024/5

Y1 - 2024/5

N2 - Adherence to customer due dates is the yardstick for the performance of manufacturing companies. In the era of same-day delivery, consumers expect reliable delivery of ordered goods and short delivery times. Also, in the field of business-to-business supply, it is evident that adherence to delivery dates is a fundamental logistical objective for companies. Contract manufacturers, in particular, are confronted with significant challenges: strong fluctuations in customer demand, shorter requested delivery times, and high competitive pressure require appropriate organisation, planning and control of production. However, companies often miss their schedule reliability targets and fail to identify the right causes for these failures. This raises the question of what factors influence the failure to meet schedule reliability targets, how to identify such factors, and what options are available to counteract them. This contribution addresses this issue and focuses on ways to analyse the emerging lateness at work systems in production areas as a deviation of the actual form the planned throughput time. We present existing approaches to analysing the lateness behaviour at work systems and extend the current theory of logistical modelling to determine the three drivers of the so-called relative lateness – planning influences, variance of work-in-process (WIP) and sequence deviations – at work systems systematically. Through this analysis, we enable the practical applicator to initiate target-oriented countermeasures to improve the schedule reliability of their work systems with acceptable analysis expenditure.

AB - Adherence to customer due dates is the yardstick for the performance of manufacturing companies. In the era of same-day delivery, consumers expect reliable delivery of ordered goods and short delivery times. Also, in the field of business-to-business supply, it is evident that adherence to delivery dates is a fundamental logistical objective for companies. Contract manufacturers, in particular, are confronted with significant challenges: strong fluctuations in customer demand, shorter requested delivery times, and high competitive pressure require appropriate organisation, planning and control of production. However, companies often miss their schedule reliability targets and fail to identify the right causes for these failures. This raises the question of what factors influence the failure to meet schedule reliability targets, how to identify such factors, and what options are available to counteract them. This contribution addresses this issue and focuses on ways to analyse the emerging lateness at work systems in production areas as a deviation of the actual form the planned throughput time. We present existing approaches to analysing the lateness behaviour at work systems and extend the current theory of logistical modelling to determine the three drivers of the so-called relative lateness – planning influences, variance of work-in-process (WIP) and sequence deviations – at work systems systematically. Through this analysis, we enable the practical applicator to initiate target-oriented countermeasures to improve the schedule reliability of their work systems with acceptable analysis expenditure.

KW - Analytical model

KW - Diagnostics

KW - Lateness

KW - Logistical performance

KW - Modelling

KW - Schedule reliability

UR - http://www.scopus.com/inward/record.url?scp=85178072252&partnerID=8YFLogxK

U2 - 10.1016/j.aime.2023.100132

DO - 10.1016/j.aime.2023.100132

M3 - Article

AN - SCOPUS:85178072252

VL - 8

JO - Advances in Industrial and Manufacturing Engineering

JF - Advances in Industrial and Manufacturing Engineering

M1 - 100132

ER -