Last Time Buy and Control Policies With Phase-Out Returns: A Case Study in Plant Control Systems

H.R. Krikke, E. van der Laan

Research output: Working paperDiscussion paperOther research output

263 Downloads (Pure)

Abstract

This research involves the combination of spare parts management and reverse logistics. At the end of the product life cycle, products in the field (so called installed base) can usually be serviced by either new parts, obtained from a Last Time Buy, or by repaired failed parts. This paper, however, introduces a third source: the phase-out returns obtained from customers that replace systems. These returned parts may serve other customers that do not replace the systems yet. Phase-out return flows represent higher volumes and higher repair yields than failed parts and are cheaper to get than new ones. This new phenomenon has been ignored in the literature thus far, but due to increased product replacements rates its relevance will grow. We present a generic model, applied in a case study with real-life data from ConRepair, a third-party service provider in plant control systems (mainframes). Volumes of demand for spares, defects returns and phase-out returns are interrelated, because the same installed base is involved. In contrast with the existing literature, this paper explicitly models the operational control of both failed- and phase-out returns, which proves far from trivial given the nonstationary nature of the problem. We have to consider subintervals within the total planning interval to optimize both Last Time Buy and control policies well. Given the novelty of the problem, we limit ourselves to a single customer, single-item approach. Our heuristic solution methods prove efficient and close to optimal when validated. The resulting control policies in the case-study are also counter-intuitive. Contrary to (management) expectations, exogenous variables prove to be more important to the repair firm (which we show by sensitivity analysis) and optimizing the endogenous control policy benefits the customers. Last Time Buy volume does not make the decisive difference; far more important is the disposal versus repair policy. PUSH control policy is outperformed by PULL, which exploits demand information and waits longer to decide between repair and disposal. The paper concludes by mapping a number of extensions for future research, as it represents a larger class of problems.
Original languageEnglish
Place of PublicationTilburg
PublisherOrganization
Number of pages41
Volume2009-66
Publication statusPublished - 2009

Publication series

NameCentER Discussion Paper
Volume2009-66

Fingerprint

Repair
Disposal
Defects
Service provider
Product lifecycle
Reverse logistics
Spare parts
Sensitivity analysis
Heuristics
Expectations management
Exogenous variables
Replacement rate
Planning
Novelty

Keywords

  • spare parts
  • reverse logistics
  • phase-out
  • PUSH-PULL repair
  • non stationary
  • Last Time Buy
  • business case

Cite this

Krikke, H. R., & van der Laan, E. (2009). Last Time Buy and Control Policies With Phase-Out Returns: A Case Study in Plant Control Systems. (CentER Discussion Paper; Vol. 2009-66). Tilburg: Organization.
Krikke, H.R. ; van der Laan, E. / Last Time Buy and Control Policies With Phase-Out Returns : A Case Study in Plant Control Systems. Tilburg : Organization, 2009. (CentER Discussion Paper).
@techreport{c1a3c4386d314147afd78b7cef171d03,
title = "Last Time Buy and Control Policies With Phase-Out Returns: A Case Study in Plant Control Systems",
abstract = "This research involves the combination of spare parts management and reverse logistics. At the end of the product life cycle, products in the field (so called installed base) can usually be serviced by either new parts, obtained from a Last Time Buy, or by repaired failed parts. This paper, however, introduces a third source: the phase-out returns obtained from customers that replace systems. These returned parts may serve other customers that do not replace the systems yet. Phase-out return flows represent higher volumes and higher repair yields than failed parts and are cheaper to get than new ones. This new phenomenon has been ignored in the literature thus far, but due to increased product replacements rates its relevance will grow. We present a generic model, applied in a case study with real-life data from ConRepair, a third-party service provider in plant control systems (mainframes). Volumes of demand for spares, defects returns and phase-out returns are interrelated, because the same installed base is involved. In contrast with the existing literature, this paper explicitly models the operational control of both failed- and phase-out returns, which proves far from trivial given the nonstationary nature of the problem. We have to consider subintervals within the total planning interval to optimize both Last Time Buy and control policies well. Given the novelty of the problem, we limit ourselves to a single customer, single-item approach. Our heuristic solution methods prove efficient and close to optimal when validated. The resulting control policies in the case-study are also counter-intuitive. Contrary to (management) expectations, exogenous variables prove to be more important to the repair firm (which we show by sensitivity analysis) and optimizing the endogenous control policy benefits the customers. Last Time Buy volume does not make the decisive difference; far more important is the disposal versus repair policy. PUSH control policy is outperformed by PULL, which exploits demand information and waits longer to decide between repair and disposal. The paper concludes by mapping a number of extensions for future research, as it represents a larger class of problems.",
keywords = "spare parts, reverse logistics, phase-out, PUSH-PULL repair, non stationary, Last Time Buy, business case",
author = "H.R. Krikke and {van der Laan}, E.",
note = "Subsequently published in the International Journal of Production Research (2011) Pagination: 41",
year = "2009",
language = "English",
volume = "2009-66",
series = "CentER Discussion Paper",
publisher = "Organization",
type = "WorkingPaper",
institution = "Organization",

}

Krikke, HR & van der Laan, E 2009 'Last Time Buy and Control Policies With Phase-Out Returns: A Case Study in Plant Control Systems' CentER Discussion Paper, vol. 2009-66, Organization, Tilburg.

Last Time Buy and Control Policies With Phase-Out Returns : A Case Study in Plant Control Systems. / Krikke, H.R.; van der Laan, E.

Tilburg : Organization, 2009. (CentER Discussion Paper; Vol. 2009-66).

Research output: Working paperDiscussion paperOther research output

TY - UNPB

T1 - Last Time Buy and Control Policies With Phase-Out Returns

T2 - A Case Study in Plant Control Systems

AU - Krikke, H.R.

AU - van der Laan, E.

N1 - Subsequently published in the International Journal of Production Research (2011) Pagination: 41

PY - 2009

Y1 - 2009

N2 - This research involves the combination of spare parts management and reverse logistics. At the end of the product life cycle, products in the field (so called installed base) can usually be serviced by either new parts, obtained from a Last Time Buy, or by repaired failed parts. This paper, however, introduces a third source: the phase-out returns obtained from customers that replace systems. These returned parts may serve other customers that do not replace the systems yet. Phase-out return flows represent higher volumes and higher repair yields than failed parts and are cheaper to get than new ones. This new phenomenon has been ignored in the literature thus far, but due to increased product replacements rates its relevance will grow. We present a generic model, applied in a case study with real-life data from ConRepair, a third-party service provider in plant control systems (mainframes). Volumes of demand for spares, defects returns and phase-out returns are interrelated, because the same installed base is involved. In contrast with the existing literature, this paper explicitly models the operational control of both failed- and phase-out returns, which proves far from trivial given the nonstationary nature of the problem. We have to consider subintervals within the total planning interval to optimize both Last Time Buy and control policies well. Given the novelty of the problem, we limit ourselves to a single customer, single-item approach. Our heuristic solution methods prove efficient and close to optimal when validated. The resulting control policies in the case-study are also counter-intuitive. Contrary to (management) expectations, exogenous variables prove to be more important to the repair firm (which we show by sensitivity analysis) and optimizing the endogenous control policy benefits the customers. Last Time Buy volume does not make the decisive difference; far more important is the disposal versus repair policy. PUSH control policy is outperformed by PULL, which exploits demand information and waits longer to decide between repair and disposal. The paper concludes by mapping a number of extensions for future research, as it represents a larger class of problems.

AB - This research involves the combination of spare parts management and reverse logistics. At the end of the product life cycle, products in the field (so called installed base) can usually be serviced by either new parts, obtained from a Last Time Buy, or by repaired failed parts. This paper, however, introduces a third source: the phase-out returns obtained from customers that replace systems. These returned parts may serve other customers that do not replace the systems yet. Phase-out return flows represent higher volumes and higher repair yields than failed parts and are cheaper to get than new ones. This new phenomenon has been ignored in the literature thus far, but due to increased product replacements rates its relevance will grow. We present a generic model, applied in a case study with real-life data from ConRepair, a third-party service provider in plant control systems (mainframes). Volumes of demand for spares, defects returns and phase-out returns are interrelated, because the same installed base is involved. In contrast with the existing literature, this paper explicitly models the operational control of both failed- and phase-out returns, which proves far from trivial given the nonstationary nature of the problem. We have to consider subintervals within the total planning interval to optimize both Last Time Buy and control policies well. Given the novelty of the problem, we limit ourselves to a single customer, single-item approach. Our heuristic solution methods prove efficient and close to optimal when validated. The resulting control policies in the case-study are also counter-intuitive. Contrary to (management) expectations, exogenous variables prove to be more important to the repair firm (which we show by sensitivity analysis) and optimizing the endogenous control policy benefits the customers. Last Time Buy volume does not make the decisive difference; far more important is the disposal versus repair policy. PUSH control policy is outperformed by PULL, which exploits demand information and waits longer to decide between repair and disposal. The paper concludes by mapping a number of extensions for future research, as it represents a larger class of problems.

KW - spare parts

KW - reverse logistics

KW - phase-out

KW - PUSH-PULL repair

KW - non stationary

KW - Last Time Buy

KW - business case

M3 - Discussion paper

VL - 2009-66

T3 - CentER Discussion Paper

BT - Last Time Buy and Control Policies With Phase-Out Returns

PB - Organization

CY - Tilburg

ER -

Krikke HR, van der Laan E. Last Time Buy and Control Policies With Phase-Out Returns: A Case Study in Plant Control Systems. Tilburg: Organization. 2009. (CentER Discussion Paper).