Work In Process Control for a High Product Mix Manufacturing System

Olaitan, Oladipupo; Yu, Qian; Alfnes, Erlend

doi:10.1016/j.procir.2017.03.352

Cited by 8 publications

(5 citation statements)

References 12 publications

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“…Providing multiple products requires flexible workstations with minimum waiting time and defective items. Kanban is seen to fulfil these objectives quite effectively as it does not allow production until there is customer demand (Olaitan, Yu, & Alfnes, 2017). Moreover, scheduling intermittent production by incorporating the Kanban system significantly reduces inventories and thus improves productivity (Bernegger & Webster, 2014).…”

Section: Kanbanmentioning

confidence: 99%

Assessing the moderating role of the extent of implementation of lean methods in predicting productivity improvement

Singla¹,

Sharma²

2023

RAUSP

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Purpose The study aims to explore the argument of implementing the lean method to part or whole of an operation by examining the moderating impact of varying levels of the extent of implementation of four different lean methods, along with their functionalities, in predicting productivity improvement (PI). Design/methodology/approach As the focus of understanding the efficacy of lean principles is shifting from process to industry level, this study tried to generalize the approach by gathering data from 132 large Indian auto component manufacturers. This involves an assessing/monitoring approach rather than measurement. Findings Results highlighted the interdependence or individuality of the extent of implementation of lean methods and their functionalities. Findings revealed a significant moderating effect in improving productivity to a greater extent of 50%. Research limitations/implications Adopting an assessment approach to a measurement study provides a noteworthy contribution to bridging theory and practical consequences. The findings can be appropriately extrapolated to medium and small enterprises forming a critical connection in the entire automobile manufacturing ecosystem. Practical implications The study showed that even if a lean method is applied to a certain extent of operations the chances of PI are significant. This is important for decision makers as they confront problems of optimum resource allocation. Social implications PI, reduced cost and generalization of results would enable the auto component industry to become more competitive. Originality/value The examination of the moderation effect of a lean principle implementation extent, along with that of its functionalities to predict the improvement in productivity from its existing level, is a major outcome of this study.

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Section: Kanbanmentioning

confidence: 99%

Assessing the moderating role of the extent of implementation of lean methods in predicting productivity improvement

Singla¹,

Sharma²

2023

RAUSP

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“…Proper handling of components and semi-finished products forming the so-called Work in Process (WIP) is suggested in [5] for reducing the lead time and improving the delivery performance of HMLV production. This work, implicitly, also emphasizes the importance of the right sizing of internal buffers.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Settings of the simulation model were determined by different lot-sizing (grouping and splitting) and sequencing rules. These rules were suggested by planners of the factory and by the literature [5,13,26,27]. The following options were investigated:…”

Section: Analyzing the Impact Of Dynamic Changesmentioning

confidence: 99%

Improving Delivery Performance in High-Mix Low-Volume Manufacturing by Model-Based and Data-Driven Methods

Gödri¹

2022

Applied Sciences

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In a high-mix and low-volume (HMLV) manufacturing environment where demand fluctuation is the rule rather than the exception, daily production management in face of conflicting key performance indicators such as high delivery precision, short lead time, and maximal resource utilization is a most challenging task. This situation may even be hampered by unreliable supplier performance. This paper presents a generic decision support workflow, which first identifies the most critical external and internal factors which have a serious impact on delivery performance. Next, it suggests a method which combines traditional manufacturing system simulation with advanced machine learning techniques to support the improved daily routine lot-sizing and production scheduling activities in a HMLV company. Argumentation is motivated and illustrated by a detailed industrial case study.

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“…The manufacturing throughput time is significantly higher than the value adding time, and it is highly variable, which makes planning difficult for the downstream assembly of the components produced. In a previous phase of the project, in which CONWIP control mechanism was applied to regulate system inventory and a sequencing rule to control production at the workstations, significant improvements were achieved in the throughput time's mean and its variation [1,2]. However, as it is the case with tighter control of inventory in manufacturing, previously unrealised problems were exposed in relation to the selection of the product model to release into the CONWIP loop.…”

Section: Introductionmentioning

confidence: 99%

“…To overcome the problem highlighted above, a CONWIP control was implemented in the sewing section to limit the volume of work in progress (WIP) in the section, with an intermediate buffer also created between the two sections. The lower amount of WIP, judging by Little's law [3], reduced the throughput time [1,2]. The intermediate buffer served decoupling purposes between the flow of items out of the cutting section and their release into the sewing section.…”

Section: Introductionmentioning

confidence: 99%

A Nested Configuration of POLCA and Generic Kanban in a High Product Mix Manufacturing System

Olaitan

Fragapane

Alfnes

et al. 2017

IFIP Advances in Information and Communication Technology

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The work presented in this paper is part of a project aimed at streamlining and improving the process flow at a leather furniture manufacturing company. The manufacturing throughput time is highly variable, and this makes planning difficult for the assembly of components at the downstream stages. Throughput time predictability at the upstream stages where the components are manufactured would facilitate the planning of their assembly according to their expected arrival times for specific product models. Research conducted in a previous phase of the project showed that the application of the CONstant Work In Progress (CONWIP) control mechanism to regulate inventory yielded significant improvements in the throughput time's mean and variation. However, as it is the case with tighter control of inventory in manufacturing, previously unrealised problems were exposed in relation to the selection of the product model to release into the CONWIP loop. This has significant impact on the balance of the distribution of workload across the system's workstations and among the multi-skilled teams at one of the workstations. This research implements a nested configuration of the Paired-cell Overlapping Loop Of Cards with Authorisation (POLCA) and the Generic Kanban control mechanisms to achieve a balance of the workloads. This ensures a synchronised flow of the different product mix through the entire manufacturing system.

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Work In Process Control for a High Product Mix Manufacturing System

Cited by 8 publications

References 12 publications

Assessing the moderating role of the extent of implementation of lean methods in predicting productivity improvement

Assessing the moderating role of the extent of implementation of lean methods in predicting productivity improvement

Improving Delivery Performance in High-Mix Low-Volume Manufacturing by Model-Based and Data-Driven Methods

A Nested Configuration of POLCA and Generic Kanban in a High Product Mix Manufacturing System

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