Lead-Time, Inventory, and Safety Stock Calculation in Job-Shop Manufacturing

Abstract

The purpose of this article is to present a method for calculating the lead-time, the inventory, and the safety stock or buffer in job shop manufacturing, which are essentially stochastic variables. The research method is quantitative modelling. The theoretical foundation of the method relies on the techniques belonging to the WLC (workload control) body of knowledge on the manufacturing management. The study includes an application of the method in a manufacturing plant of the furniture industry, whose operation strategy requires high dependability. The company operates in a supply chain and must have high a reliability in deliveries. Adequate safety stocks, lead times, and inventory levels provide the protection against the lack of reliability in the deliveries. The inventory should remain within a certain range, being as small as possible to maintain low lead times, but not too small that it could provoke a starvation, configuring an optimization problem. The study offers guidelines for a complete application in industries. Further research shall include the influence of the variability of the lot size in the stochastic variables.

Workload Control and Order Dispatching Rules

“…The literature recognises the need for more empirical research on practical implementations of the WLC concept (Sagawa and Land, 2018) since they still represent a small part of the articles published in the area (Silva et al, 2015). Some previous papers such as Sellitto (2018) present theoretical models to help calculate WLC parameters in real-world applications. On the other hand, papers such as Thürer et al (2016a) rely on simulation to evaluate LT and tardiness associated with WLC techniques.…”

“…The study addresses the input control mechanism, as recent studies have focused particularly on output controls (Land et al, 2015). Although the original focus of WLC was on highly balanced production lines, a more recent study states that the WLC could also be effective on unbalanced manufacturing plants (Sellitto, 2018), which is the current case. In such cases, particular attention should be paid to non-critical resources, since they help to protect the critical ones (Fernandes et al, 2020).…”

“…The model includes Eqs. (1) to ( 9) and handles isolated work centers as well as complete production lines (Sellitto, 2018):…”

Material handling and order release control in high-variety make-to-order shops: an assessment by simulation

“…Given its importance, a broad literature exists on the performance of order release methods, such as Workload Control, both in practice (e.g. Hendry et al 2013;Silva et al 2015;Perona et al 2016;Huang 2017;Sellitto 2018;Hutter et al 2018) and using simulation (e.g. Portioli-Staudacher and Tantardini 2011;Thürer et al 2012Thürer et al , 2014Thürer et al , 2021Fernandes et al 2016Fernandes et al , 2020Gonzalez-R et al 2018;Haeussler and Netzer 2020).…”

Material Requirement Planning Information System: Prototype And Lead Time Analysis

“…Lead Time Analysis, a technique in supply chain management, examines the duration a product or material requires to transition from order placement to customer delivery, encompassing the complete span between these two junctures. Different manufacturing control levels influence lead times and play a vital role in establishing control parameters, such as lead time offsets, within Material Requirements Planning (MRP) systems[21]. Integrating technology and automation tools is closely intertwined with Lead Time Analysis, as it significantly reduces lead times[22].…”