The impact of supply lead-time on the value of Vendor Managed Inventory in an auto-correlated demand environment

Author(s):  
Zainab Belalia ◽  
Fouzia Ghaiti
2019 ◽  
Vol 6 (1) ◽  
pp. 48-50
Author(s):  
Ikram Uddin

This study will explain the impact of China-Pak Economic Corridor (CPEC) on logistic system of China and Pakistan. This project is estimated investment of US $90 billion, CPEC project is consists of various sub-projects including energy, road, railway and fiber optic cable but major portion will be spent on energy. This project will start from Kashgar port of china to Gwadar port of Pakistan. Transportation is sub-function of logistic that consists of 44% total cost of logistic system and 20% total cost of production of manufacturing and mainly shipping cost and transit/delivery time are critical for logistic system. According to OEC (The Observing Economic Complexity) currently, china is importing crude oil which 13.4% from Persian Gulf. CPEC will china for lead time that will be reduced from 45 days to 10 days and distance from 2500km to 1300km. This new route will help to china for less transit/deliver time and shipping cost in terms of logistic of china. Pakistan’s transportation will also improve through road, railway and fiber optic cabal projects from Karachi-Peshawar it will have speed 160km per hour and with help of pipeline between Gwadar to Nawabshah gas will be transported from Iran. According to (www.cpec.inf.com) Pakistan logistic industry will grow by US $30.77 billion in the end of 2020.


2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1877.2-1878
Author(s):  
S. Mackie ◽  
A. Barr ◽  
A. Cracknell ◽  
S. Farrell ◽  
J. Parvin ◽  
...  

Background:In our large, multi-site hospital, patients with suspected GCA are started promptly on high-dose prednisolone but until 2019, patients waited for temporal artery biopsy (TAB) until the GCA diagnosis could be confirmed (“GCA”) or refuted (“not-GCA”). Reports of the impact of introducing temporal and axillary artery ultrasound (TAUS) have mainly come from smaller hospitals. Agreement between TAUS and TAB has been reported by others with a Cohen’s kappa of 0.35 [1] and 0.40 [2]. We used Lean methodology to identify metrics across 5 key domains: delivery, quality, service, morale and cost.Objectives:To design metrics for a service evaluation to measure impact of introducing TAUS, and to test their feasibility of measurement within routine care.Methods:Our primary driver was time from presenting to our service to diagnostic confirmation (lead time). Pathway mapping, value stream mapping and a driver diagram identified key ideas for improvement.We chose to measure: Delivery (mean lead time for each month), Quality (proportion of patients with GCA and positive TAB/TAUS; total (cumulative) prednisolone dose in patients with not-GCA, Service (patient feedback), Morale (staff feedback) and Cost (number of patients; cost of tests per patient; overall costs). We plotted these by month on run charts and defined a significant shift as 6 consecutive monthly values below baseline median. Cohen’s kappa was calculated using GraphPad QuickCalcs.Results:Routine TAUS for suspected GCA was introduced from January 2019, alongside a multidisciplinary team monthly meeting. TAUS was done a median of 2.5 days from referral. Agreement between TAB and TAUS results was good (Table 1). The run chart showed a significant shift in our Delivery (median lead time fell from 28.7 days to 21 days after introduction of ultrasound) and both Quality metrics (proportion of GCA with positive TAB/TAUS increased from 29% to 69%; total prednisolone dose for not-GCA fell from 1.335g to 0.846g).Table 1.Concordance between temporal and axillary artery ultrasound (TAUS) and temporal artery biopsy (TAB) in scans performed through 2019. Cohen’s weighted kappa 0.59 (including equivocal results as separate category).TAUS positiveTAUS negativeTAUS equivocalTAB positive1411TAB negative5275TAB equivocal030Within Costs, average per-patient costs of TAB/TAUS declined from £1004/patient to £792/patient, but total referrals for TAB/TAUS increased from 6/month to 10/month, increasing overall costs. Staff and patient feedback (Service, Morale) revealed that further improvements to the care pathway were needed to manage the additional complexity.Conclusion:Lean methodology identified multiple metrics for evaluating the impact of TAUS on our service. Introducing TAUS improved Delivery and Quality, but measuring Costs, Morale and Service helped identify unintended consequences. Concordance between TAUS and TAB was good. We plan to continue to improve and monitor the care pathway based on our multi-stakeholder feedback.References:[1]Luqmani et al., HTA 2016[2]Mukhtyar et al., Clin Rheum 2019Disclosure of Interests:Sarah Mackie Grant/research support from: Roche (attendance of EULAR 2019; co-applicant on research grant), Consultant of: Sanofi, Roche/Chugai (monies paid to my institution not to me), Andrew Barr: None declared, Alison Cracknell: None declared, Shannon Farrell: None declared, Jimmy Parvin: None declared, Ajay Patil: None declared, Ian Simmons: None declared, Kate Smith Grant/research support from: Medical education grants from Sanofi and Biogen, Speakers bureau: Novartis, Andrea Sweeting: None declared, Max Troxler: None declared, Tara Webster: None declared, Richard Wakefield Speakers bureau: Novartis, Janssen, GE


2017 ◽  
Vol 8 (2) ◽  
pp. 30-40 ◽  
Author(s):  
Peter Nielsen ◽  
Zbigniew Michna ◽  
Brian Bruhn Sørensen ◽  
Ngoc Do Anh Dung

AbstractLead times and their nature have received limited interest in literature despite their large impact on the performance and the management of supply chains. This paper presents a method and a case implementation of the same, to establish the behavior of real lead times in supply chains. The paper explores the behavior of lead times and illustrates how in one particular case they can and should be considered to be independent and identically distributed (i.i.d.). The conclusion is also that the stochastic nature of the lead times contributes more to lead time demand variance than demand variance.


2020 ◽  
Vol 90 (19-20) ◽  
pp. 2304-2321
Author(s):  
Olivia Ho-Yi Fung ◽  
Joanne Yip ◽  
Mei-Chun Cheung ◽  
Kit-Lun Yick ◽  
Kenny Yat-Hong Kwan ◽  
...  

Bracing is the most common non-operative treatment option for patients with adolescent idiopathic scoliosis (AIS). However, existing brace designs have deficiencies, including a long production lead time and low patient compliance caused by the negative impacts of bracing on quality of life (QoL). The aim of this study was to address these problems by developing a new textile-based scoliosis brace in accordance with the biomechanics used in the existing braces for spinal correction. A case study of interface pressure had been carried out to determine the optimum combination of pads to be used in the proposed brace to correct a scoliotic spine. AIS patients who were undergoing hard brace treatment were recruited to complete a questionnaire (BrQ) on hard braces and on the proposed brace. The BrQ scores of the two types of braces were compared to assess their respective impacts on the QoL. The findings show that the proposed brace can address the issue of patient compliance by reducing the impact of bracing on QoL, and shorten the production lead time through incorporation of the mass customization concept into the design. Similar to most of the commonly-used scoliosis braces, the selected combination of pads used in the proposed brace for spinal correction shows a sufficient amount of exerted pressure and a similar function of active spinal correction.


Author(s):  
Siang Li Chua ◽  
Wai Leng Chow

No-shows are patients who miss scheduled Specialist Outpatient Clinic (SOC) appointments. No-shows can impact patients' access to care and appointment lead time. This chapter describes a data-driven strategy of improving access to specialist care through first developing a stratified predictive scoring model to identify patients at risk of no-shows; second, studying the impact of a dynamic overbooking strategy that incorporates the use of the no-show prediction model using discrete event simulation (DES) on lead time. Seventeen variables related to new SOC appointments for subsidized patients in 2016 were analyzed. Multiple logistic regression (MLR) found eight variables independently associated with no-shows with area under receiver operation curve (AUC) 70%. The model was tested and validated. DES model simulated the appointment overbooking strategy as applied to the top highest volume specialties and concluded that lead time of Specialty 1 and 2 can be shortened by 27.5 days (49% improvement) and 21.3 (33%) respectively.


2009 ◽  
Vol 2009 ◽  
pp. 1-27 ◽  
Author(s):  
Khaled Hadj Youssef ◽  
Christian van Delft ◽  
Yves Dallery

We consider a single-stage multiproduct manufacturing facility producing several end-products for delivery to customers with a required customer lead-time. The end-products can be split in two classes: few products with high volume demands and a large number of products with low-volume demands. In order to reduce inventory costs, it seems efficient to produce the high-volume products according to an MTS policy and the low volume products according to an MTO policy. The purpose of this paper is to analyze and compare the impact of the scheduling policy on the overall inventory costs, under customer lead-time service level constraints. We consider two policies: the classical FIFO policy and a priority policy (PR) which gives priority to low volume products over high volume products. We show that for some range of parameters, the PR rule can significantly outperform the FIFO rule. In these ranges, the service level constraints are satisfied by the PR rule with much lower inventory costs.


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