Operational Metrics Research Articles

In Vivo Evaluation of Oxygenic Photogranules’ Photosynthetic Capacity by Pulse Amplitude Modulation and Phototrophic–Irradiance Curves

The commingled microbial moiety of oxygenic photogranules (OPGs) facilitates aeration-free wastewater treatment. Embedded in an extracellular polymeric substances (EPS) matrix, microbial producers and consumers of oxygen occupying granular niches exchange substrates among themselves and with the bulk fluid. An assessment of the OPG’s phototrophic potential or functional capacity may require combining different photoactivity signals. The photosynthetic capacity was evaluated using photosynthetic oxygen evolution (POE) and chlorophyll fluorescence (rapid light curves, RLC) measurements using OPGs grown at different light intensities.. A maximum oxygen generating capacity for optimal OPGs and reactor conditions was determined to be 284.4 mgO2 gVSS–1 h–1 The OPGs exhibited photoelasticity, with higher photosynthetic capacity in high light (HL) compared to that in low light (LL) adapted samples. Saturation irradiances before the onset of photoinhibition for LL and HL samples were 1000 and 1200 μmol m–2 s–1, respectively using POE signals, and 478 μmol m–2 s–1 and 611 μmol m–2 s–1 using RLC signals. Moreover, HL adapted samples had higher nonphotochemical quenching rates which allude to the OPG’s photoelastic potential. The correlation coefficients (κ) between POE and RLCs were lower than reported values for pure microbial cultures reflecting the enhanced contribution from different photosynthetic clades with a variety of light-harvesting pigments present in OPGs. In an OPG reactor, the photochemical activity can be influenced by the granular size, granular ecology, and reactor operation metrics related to irradiance interactions such as mixing, self-shading, light intensity, photoperiods, and reactor depth. This presents opportunities for design of intensive wastewater resource recovery using phototrophic granular biomass.

Optimal degradation-based hybrid double-stage acceptance sampling plan for a heterogeneous product

Units of a product, even though produced in the same batch, may perform differently due to a variety of randomness in raw materials, manufacturing process and repair actions (e.g., refurbishment). If these units are also stored for a long period of time, their key characteristics will degrade randomly during storage. As a result, the product will exhibit heterogeneous performance upon delivery. Such a heterogeneity significantly affects the product's acceptability and is one of the utmost concerns to both the producer and consumer. In this study, we propose a degradation-based hybrid double-stage acceptance sampling plan (DHDASP) to determine the acceptability for a product exhibiting heterogeneous performance. Compared to ordinary acceptance sampling plans, the new plan provides the producer with a higher likelihood of product acceptability and offers the consumer an opportunity to explore the product's operational reliability metrics without unnecessary discard of units. In practice, it will balance the benefits of the producer and consumer and meanwhile, accurately assess the product's reliability metrics under flexible testing scenarios. A numerical study verifies the advantages and higher efficiency of the DHDASP over commonly used alternatives in handling heterogeneous products.

Laparoscopic-assisted ERCP following RYGB: a 12-year assessment of outcomes and learning curve at a high-volume pancreatobiliary center.

Treatment of pancreaticobiliary pathology following Roux-en-Y gastric bypass (RYGB) poses significant technical challenges. Laparoscopic-assisted endoscopic retrograde cholangiopancreatography (LA-ERCP) can overcome those anatomical hurdles, allowing access to the papilla. Our aims were to analyze our 12-year institutional outcomes and determine the learning curve for LA-ERCP. A retrospective review of cases between 2007 and 2019 at a high-volume pancreatobiliary unit was performed. Logistic regression was used to identify predictors of specific outcomes. To identify the learning curve, CUSUM analyses and innovative methods for standardizing the surgeon's timelines were performed. 131 patients underwent LA-ERCP (median age 60, 81% females) by 17 surgeons and 10 gastroenterologists. Cannulation of the papilla was achieved in all cases. Indications were choledocholithiasis (78%), Sphincter of Oddi dysfunction/Papillary stenosis (18%), management of bile leak (2%) and stenting/biopsy of malignant strictures (2%). Median total, surgical and ERCP times were 180, 128 and 48min, respectively, and 47% underwent concomitant cholecystectomy. Surgical site infection developed in 9.2% and post-ERCP pancreatitis in 3.8%. Logistic regression revealed multiple abdominal operations and magnitude of BMI decrease (between RYGB and LA-ERCP) to be predictive of conversion to open approach. CUSUM analysis of operative time demonstrated a learning curve at case 27 for the surgical team and case 9 for the gastroenterology team. On binary cut analysis, 3-5 cases per surgeon were needed to optimize operative metrics. LA-ERCP is associated with high success rates and low adverse events. We identify outcome benchmarks and a learning curve for new adopters of this increasingly performed procedure.

Palliative Care Consultation in Hospitalized Patients With COVID-19: A Retrospective Study of Characteristics, Outcomes, and Unmet Needs

ContextFew studies have described the characteristics and palliative care needs in hospitalized patients with coronavirus disease 2019 (COVID-19). ObjectivesDescribing characteristics, consultation demands, patients’ needs, and outcomes of hospitalized patients with COVID-19 who received a palliative care evaluation. MethodsRetrospective chart review of patients (aged 18+ years) with COVID-19 admitted to an academic quaternary center and seen by the geriatrics and palliative medicine team from March 1st to May 11th, 2020. Socio-demographics, operational metrics, severity of illness, goals of care-advanced care planning documentation, and outcomes were analyzed. ResultsThree hundred seventy-six (17.6%) out of 2138 COVID-19 admissions were seen by the consultation team. Compared with prepandemic situation (September 1st, 2019, to February 29th, 2020), overall new consults (205 vs. 371, P < 0.001) significantly increased, particularly in the intensive care unit (ICU; 9.5% vs. 36.9%, P < 0.001). For the COVID-19 population, median age was 78 years (interquartile range, 70-87; range, 36-102); 56% were male. LACE score, D-dimer, and C-reactive protein suggested severe disease and increased risk of mortality. Seventy-five percent of consults were for goals of care-advanced care planning, and 9.6% for symptoms. During the index admission, 7.1% had documented advanced directives, and 69.7% became do not resuscitate. Of all deaths, 55.5% were in the ICU, and 87.2% were aged ≥65 years. Underserved minority patients had a disproportionate mortality. Overall consultation mortality (38.3% vs. 70.4%, P < 0.001) and ICU mortality (55.2% vs. 78.1%, P < 0.001) significantly increased compared with those before COVID-19. ConclusionDuring this pandemic, understanding inpatient specialized palliative care needs and the vulnerable populations driving these causes may encourage health-care agencies and local, state, and federal governments to support the dedicated palliative care workforce.

The effect of a nursing strike on emergency department operational metrics.

In July of 2017, after more than 15 months of negotiations, an academic teaching hospital in Boston failed to reach an agreement on the terms of contract renewal with its nursing union resulting in a strike. Replacement nurses were hired by the hospital to fulfill nursing duties for five days. This study aims to measure the effects of this nursing strike on the patients seen in the emergency department (ED) by examining operational metrics before and during the strike. Retrospective analysis of patient visits occurring for the five days of the strike (July 12-16, 2017) compared with the analogous five-day period immediately preceding that of the strike (July 5-9, 2017). During the strike, ED volume decreased by 23.6% (691 vs. 528 visits), and the decrease was more pronounced for adult vs. pediatric visits. There were no differences in patient sex, race/ethnicity or age groups. EMS transports decreased by 49.1% (171 vs. 87 transports). Although patient dispositions were similar in both periods, length of stay decreased for discharged patients (median 204 vs 178 minutes, p=0.01), and did not change significantly for admitted patients (median 322 vs. 320 minutes, p=0.33). There was one patient death in each of the periods. Although rare, nursing strikes do occur. These data may be useful for hospitals preparing for a strike.

Development and protocol for a nurse-led telephonic palliative care program

BackgroundThe COVID-19 pandemic has resulted in a profound transformation of health care delivery toward telemedicine models.PurposeWe present the structure of a nurse-led telephonic palliative program and operational metrics to influence further development of tele-palliative programs.MethodsThe nurses engage with seriously ill patients for 6 months with the goal of discussing advance care planning (ACP) and addressing self-identified issues related to their illness.FindingsOf the first 100 program graduates, 78% were actively engaged and 51% named a health care agent and/or engaged in ACP. Of the 18 patients who died during the study, 13 (72%) were enrolled in hospice services.DiscussionOur preliminary results indicate that seriously ill patients are willing to engage with nurses and to participate with discussions on ACP.ConclusionGiven the gaps in health care exposed by the COVID-19 pandemic, this innovative program serves as an important model for bringing palliative care directly to patients.

Evaluation of electronic health record-integrated digital health tools to engage hospitalized patients in discharge preparation.

To evaluate the effect of electronic health record (EHR)-integrated digital health tools comprised of a checklist and video on transitions-of-care outcomes for patients preparing for discharge. English-speaking, general medicine patients (>18 years) hospitalized at least 24 hours at an academic medical center in Boston, MA were enrolled before and after implementation. A structured checklist and video were administered on a mobile device via a patient portal or web-based survey at least 24 hours prior to anticipated discharge. Checklist responses were available for clinicians to review in real time via an EHR-integrated safety dashboard. The primary outcome was patient activation at discharge assessed by patient activation (PAM)-13. Secondary outcomes included postdischarge patient activation, hospital operational metrics, healthcare resource utilization assessed by 30-day follow-up calls and administrative data and change in patient activation from discharge to 30 days postdischarge. Of 673 patients approached, 484 (71.9%) enrolled. The proportion of activated patients (PAM level 3 or 4) at discharge was nonsignificantly higher for the 234 postimplementation compared with the 245 preimplementation participants (59.8% vs 56.7%, adjusted OR 1.23 [0.38, 3.96], P = .73). Postimplementation participants reported 3.75 (3.02) concerns via the checklist. Mean length of stay was significantly higher for postimplementation compared with preimplementation participants (10.13 vs 6.21, P < .01). While there was no effect on postdischarge outcomes, there was a nonsignificant decrease in change in patient activation within participants from pre- to postimplementation (adjusted difference-in-difference of -16.1% (9.6), P = .09). EHR-integrated digital health tools to prepare patients for discharge did not significantly increase patient activation and was associated with a longer length of stay. While issues uncovered by the checklist may have encouraged patients to inquire about their discharge preparedness, other factors associated with patient activation and length of stay may explain our observations. We offer insights for using PAM-13 in context of real-world health-IT implementations. NIH US National Library of Medicine, NCT03116074, clinicaltrials.gov.

Interdisciplinary, Innovative, and International: Nursing and Engineering Technology Students Creating New Patient Technology.

This article describes an innovative interdisciplinary project that partnered nursing and engineering technology students. The students constructed patient transfer and mobility technology that addressed crucial operational, safety, and usability metrics. The final constructed prototype was presented to an international audience during a two-week study abroad. The project was designed to explore the development of effective interdisciplinary teamwork, recognition of discipline-specific expertise, and a greater understanding of the global health care environment. Qualitative content analysis design was used to determine the impact on leadership development, effective team synergy, and the global health care experience.

Payment Models to Coordinate Healthcare Providers with Partial Attribution of Outcome Costs

Problem definition: In many healthcare systems, general practitioners refer patients to specialists, who make treatment decisions under limited capacity. We evaluate the effectiveness of different payment schemes, both traditional ones, where the payer contracts separately with the providers, and bundled schemes, where the providers share a single bundled payment. A key feature considered is a performance-based payment component to coordinate the decisions of the general practitioner and specialist by a single payer. The providers are partially responsible for the patient outcomes and costs stemming from their treatment decisions. Academic/practical relevance: We propose and analyze a model to address how referral and specialist treatment decisions in healthcare impact each other and how payment schemes impact the coordination of care between the general practitioner and specialist. Our work is valuable to policymakers in understanding the trade-offs between using bundled and unbundled payment schemes in a referral-based healthcare system. Methodology: The underlying research method is the analysis of optimization models (with congestion effects embedded) to explore the effects of different payment schemes on different entities and various operational performance measures in a healthcare system. Results: A bundled scheme has higher referral rates, lower time spent with the patient by the specialist, higher specialist utilization relative to an unbundled system in most scenarios, and higher system costs. Our conclusions are robust to various model changes. Managerial implications: Our work provides specific managerial insights into the relative performance of bundled and unbundled payment systems on operational metrics in a referral-based healthcare system. It also sheds light on how the level of attributability of service outcomes to providers interacts with payment schemes to influence referral and specialist treatment decisions and impact various quality and cost metrics.

Appendectomy Hospital Stay: No Difference in Obese Adult or Pediatric Patient Length of Stay Compared to Nonobese Patients.

Background: Studies of adult and pediatric patients undergoing appendectomy have reported variable outcomes and operative metrics related to the effect of obesity. The purpose of this study was to investigate the effect of obesity in adult and pediatric patients undergoing appendectomy at our institution.Methods: This single-center retrospective study evaluated the relationship between length of hospital stay for appendectomy and body mass index (BMI). Data obtained from the electronic medical record included age, sex, weight, height, BMI, the number of hours the patient experienced symptoms prior to presentation to the emergency room, the number of hours the patient was admitted prior to surgery, the number of hours of hospital admission after surgery, perforated appendix, preoperative comorbidities, and evidence of preoperative sepsis.Results: During the 3-year study period, 118 adults and 38 children who underwent appendectomy composed the study groups. Patients were stratified by obese and nonobese, with obesity defined as BMI ≥30.0 kg/m2. In adults, we found no significant difference between length of stay in obese (n=45) and nonobese (n=73) patients (79.6 ± 65.5 hours vs 101.6 ± 123.0 hours; P=0.21). In children, we found no significant difference between length of stay in obese (n=9) and nonobese (n=29) patients (92.9 ± 64.6 hours vs 109.0 ± 93.5 hours; P=0.54).Conclusion: Obesity did not affect length of stay in adults and children who underwent appendectomy in the present series.

Use of Bulk Industrial Wastes in the Production of Glass Foam Materials

Research on the recycling of bulk industrial wastes in the production of granular and block foam materials is reviewed. The possibilities and prospects for obtaining materials with high technical and operational metrics and environmental load reduction are shown discussed.

Cloud Electricity Storage for Multi-Service Battery Operation: Case of RTE

Problem definition: We study a cloud storage operator that provides shared storage service for electricity end-users using the residual part of a multi-service grid-scale battery primarily used for high-priority grid services. We design an optimal product with regard to pricing and customer portfolio. Academic/practical relevance: A framework and solution approach for assessing and operating such multi-service battery operations with stochastic services and different priority levels is an open problem. Methodology: We model the problem as a two-stage stochastic optimization between high-priority stochastic grid services and low-priority cloud storage for stochastic end-users. We also propose operational metrics of multiplexing gain and probability of blocking to assess the operation of the multi-service multi-user battery. To address the computational challenge of solving the stochastic optimization with a large number of end-users, we propose effective capacity as a convex approximation that allows an analytical solution. We then provide an empirical analysis based on real grid congestion data from RTE France and a large dataset of end-users' electricity consumption in California. Results: Our empirical analysis shows (i) our proposed effective capacity is a close approximation, (ii) battery operation and profit are sensitive to the cost of external resources, number of end-users, and the leasing price of the battery, and (iii) with only a slight discount of the leasing price (~1%), the profit of the third party from a stochastic residual battery can be the same as that from a deterministic one. Managerial implications: Cloud storage as a low-priority service can profitably exist alongside other high-priority battery services, making integration of more storage in the grid economically viable and allowing larger intermittent renewables, a key path towards reduced carbon emissions.

Defining the learning curve for robotic pancreaticoduodenectomy at a single center with an established laparoscopic pancreaticoduodenectomy program

Presenter: Isabel DeLaura BS | Duke University Medical Center Background: Robotic pancreaticoduodenectomy (RPD) is a complex operation with a well-studied but inconsistent learning curve of approximately 30-250 cases. The learning curve for laparoscopic pancreaticoduodenectomy (LPD) using a team approach at Duke University has previously been reported and defined as 50 cases to reach proficiency. This study aims to compare the experience building the laparoscopic and robotic pancreaticoduodenectomy programs and to determine whether the transition from LPD to RPD shortened the learning curve for RPD. Methods: LPD and RPD cases performed at Duke University Hospital were retrospectively analyzed. Continuous operative, pathologic, and perioperative metrics from LPD and RPD were compared with independent t-test or Wilcoxon rank sum test, while categorical variables used Fisher’s exact test. Learning curves were defined with respect to OR time using CUSUM analysis. Distinct phases on the CUSUM plots for LPD and RPD were determined at clear transitions in the slope of the CUSUM fitline. Results: Thirty-nine LPD and 69 RPD were included in our analysis. Three LPD and 0 RPD were converted to open. Introduction of LPD was completed first as a hybrid technique including laparoscopic resection and open reconstruction for 23 cases (excluded from this analysis), followed by total LPD. Based on operative time, LPD had an apparent bimodal or inverted learning curve likely accounting for proficiency attained from hybrid LPD and introduction of additional surgeons and trainees later in the experience. The learning curve for RPD had an accelerated early experience phase (case 1-10), a skill consolidation phase (case 11-40), followed by an improvement phase marked by reduction in operative time (case 41-69). Compared to LPD, RPD had a shorter operative time (median 379 vs 406 minutes, p<0.03), improved LN harvest (median 15 vs 19, p<0.02), and similar estimated blood loss (EBL) (median 250ml vs 400ml, p = 0.26) and R0 resection (83% vs 85%, p = 1.0). Additionally, RPD had improved LOS (median 7 days vs 9 days, p<0.002), and lower rates of surgical site infection (10% vs 38% p<0.001), abscess (7% vs 23%, p<0.04), and readmission (13% vs 33%, p<0.03). Conclusion: Adoption of LPD can be safely performed by surgeons with experience in complex laparoscopic procedures. The transition of a competent robotic surgeon from LPD to RPD is facilitated by prior familiarity with MIS approaches to pancreatic resection which result in an abbreviated learning curve. Adoption of robotics can improve surgical quality and perioperative outcomes including operative time, LN harvest, LOS, post-operative infection, and readmission. As exposure to robotics within General Surgery, Hepatopancreatobiliary, and Surgical Oncology training programs increase, surgical quality and patient outcomes will be further improved using RPD over LPD.

Intensity of Intraoperative Spinal Cord Hyperechogenicity as a Novel Potential Predictive Indicator of Neurological Recovery for Degenerative Cervical Myelopathy.

ObjectiveTo analyze the correlations between intraoperative ultrasound and MRI metrics of the spinal cord in degenerative cervical myelopathy and identify novel potential predictive ultrasonic indicators of neurological recovery for degenerative cervical myelopathy.Materials and MethodsTwenty-two patients who underwent French-door laminoplasty for multilevel degenerative cervical myelopathy were followed up for 12 months. The Japanese Orthopedic Association (JOA) scores were assessed preoperatively and 12 months postoperatively. Maximum spinal cord compression and compression rates were measured and calculated using both intraoperative ultrasound imaging and preoperative T2-weight (T2W) MRI. Signal change rates of the spinal cord on preoperative T2W MRI and gray value ratios of dorsal and ventral spinal cord hyperechogenicity on intraoperative ultrasound imaging were measured and calculated. Correlations between intraoperative ultrasound metrics, MRI metrics, and the recovery rate JOA scores were analyzed using Spearman correlation analysis.ResultsThe postoperative JOA scores improved significantly, with a mean recovery rate of 65.0 ± 20.3% (p < 0.001). No significant correlations were found between the operative ultrasound metrics and MRI metrics. The gray value ratios of the spinal cord hyperechogenicity was negatively correlated with the recovery rate of JOA scores (ρ = −0.638, p = 0.001), while the ventral and dorsal gray value ratios of spinal cord hyperechogenicity were negatively correlated with the recovery rate of JOA-motor scores (ρ = −0.582, p = 0.004) and JOA-sensory scores (ρ = −0.452, p = 0.035), respectively. The dorsal gray value ratio was significantly higher than the ventral gray value ratio (p < 0.001), while the recovery rate of JOA-motor scores was better than that of JOA-sensory scores at 12 months post-surgery (p = 0.028).ConclusionFor degenerative cervical myelopathy, the correlations between intraoperative ultrasound and preoperative T2W MRI metrics were not significant. Gray value ratios of the spinal cord hyperechogenicity and dorsal and ventral spinal cord hyperechogenicity were significantly correlated with neurological recovery at 12 months postoperatively.

Maintaining Equity and Access: Successful Implementation of a Virtual Kidney Transplantation Evaluation

Maintaining access to kidney transplantation during a pandemic is a challenge, particularly for centers that serve a large rural and minority patient population with an additional burden of travel. The aim of this article was to describe our experience with the rollout and use of a virtual pretransplantation evaluation platform to facilitate ongoing transplant waitlisting during the early peak of the COVID-19 pandemic. This is a retrospective analysis of the process improvement project implemented to continue the evaluation of potential kidney transplantation candidates and ensure waitlist placement during the COVID-19 pandemic. Operational metrics include transplantation volume per month, referral volume per month, pretransplantation patients halted before completing an evaluation per month, evaluations completed per month, and patients waitlisted per month. Between April and September 2020, a total of 1,258 patients completed an evaluation. Two hundred and forty-seven patients were halted during this time period before completing a full evaluation. One hundred and fifty-two patients were presented at selection and 113 were placed on the waitlist. In addition, the number of patients in the active referral phase was able to be reduced by 46%. More evaluations were completed within the virtual platform (n=930 vs n= 880), yielding similar additions to the waitlist in 2020 (n= 282) vs 2019 (n= 308) despite the COVID-19 pandemic. The virtual platform allowed continued maintenance of a large kidney transplantation program despite the inability to have in-person visits. The value of this platform will likely transform our approach to the pretransplantation process and provides an additional valuable method to improve patient equity and access to transplantation.

Innovative decision support model for construction supply chain performance management

Supply chain management covers suppliers, manufacturers, distributors, and retailers linked by financial and information frameworks that require analysis, monitoring, and improvement of the performance regularly. This study presents a hybrid model of strategical and operational metrics to support managers through a clear and risk-free decision making process based on performance. Four methods which are Analytic Network Process (ANP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Decision-Making Trial and Evaluation Laboratory (DEMATEL) are proposed as an integrated approach. All performance metrics are taken from the latest version of Supply Chain Operations Reference (SCOR) model for standardisation. A real-world construction management example is applied as case study and results of application show that the proposed model is superior to the traditional models in terms of its improved decision quality. Cash Cycle Time, Return on Working Capital and Perfect Order Fulfilment were the most important performance metrics.

Energetics Metrics for Foam-Glass Concrete Building Products

The results of studies of the operational metrics of samples of foam-glass concrete building products are reported. To have a clear picture of a product’s operational capabilities under different conditions the metrics are conventionally divided into strength and energetics. The strength metrics consist of density and strength in compression and the energetics metrics consist of thermal conductivity and moisture resistance. The qualitative effects of the main parameters of the main product filler — ground glass — on the operational metrics were studied. Nomograms were developed for making a judicious choice of the input metrics of products in application to different technical and operational requirements.

Predictors of Delayed Recognition of Critical Illness in Emergency Department Patients and Its Effect on Morbidity and Mortality

Timely recognition of critical illness is associated with improved outcomes, but is dependent on accurate triage, which is affected by system factors such as workload and staffing. We sought to first study the effect of delayed recognition on patient outcomes after controlling for system factors and then to identify potential predictors of delayed recognition. We conducted a retrospective cohort study of Emergency Department (ED) patients admitted to the Intensive Care Unit (ICU) directly from the ED or within 48 hours of ED departure. Cohort characteristics were obtained through electronic and standardized chart abstraction. Operational metrics to estimate ED workload and volume using census data were matched to patients' ED stays. Delayed recognition of critical illness was defined as an absence of an ICU consult in the ED or declination of ICU admission by the ICU team. We employed entropy-balanced multivariate models to examine the association between delayed recognition and development of persistent organ dysfunction and/or death by hospitalization day 28 (POD+D), and multivariable regression modeling to identify factors associated with delayed recognition. Increased POD+D was seen for those with delayed recognition (OR 1.82, 95% CI 1.13-2.92). When the delayed recognition was by the ICU team, the patient was 2.61 times more likely to experience POD+D compared to those for whom an ICU consult was requested and were accepted for admission. Lower initial severity of illness score (OR 0.26, 95% CI 0.12-0.53) was predictive of delayed recognition. The odds for delayed recognition decreased when ED workload is higher (OR 0.45, 95% CI 0.23-0.89) compared to times with lower ED workload. Increased POD+D is associated with delayed recognition. Patient and system factors such as severity of illness and ED workload influence the odds of delayed recognition of critical illness and need further exploration.

The effects of quantity discounts on supply chain performance: Looking through the Bullwhip lens

Quantity discounts are a common pricing mechanism to stimulate large orders. We explore their impact on the dynamic behaviour of production and distribution systems by studying key operational and economic metrics. In a three-echelon supply chain, we observe that the discount generally increases the Bullwhip Effect, which especially harms the manufacturer. The discount also reduces the retailer’s purchase costs, but increases its inventory- and capacity-related costs. A key trade-off thus emerges, which manifests itself through a U-shaped relationship between the total cost and the discount acceptance parameter. In the light of this trade-off, we discuss how key factors should affect the retailer’s willingness to pursue the discount. We observe that managers that need to deal with tougher environmental conditions, such as high demand uncertainty and long lead times, should be less reluctant to increase orders up to the discount quantity. We also discuss in detail other valuable insights for professionals, both from the perspective of sellers and buyers.

Operationalizing digital twins through model‐based systems engineering methods

AbstractIn recent years there has been increased demand for readiness and availability metrics across many industries and especially in national defense to enable data‐driven decision making at all levels of planning, maintenance, and operations, and in leveraging integrated models that inform stakeholders of current operational system health and performance metrics. The digital twin (DT) has been identified as a promising approach for deploying these models to fielded systems although several challenges exist in wide adoption and implementation. Two challenges examined in this article are that the nature of DT development is a system‐specific endeavor, and the development is usually an additional effort that begins after initial system fielding. A fundamental challenge with DT development, which sets it apart from traditional models, is the DT itself is treated as a separate system, and therefore the physical asset/DT construct becomes a system‐of‐systems problem. This article explores how objectives in DT development align with those of model‐based systems engineering (MBSE), and how the MBSE process can answer questions necessary to define the DT. The key benefits to the approach are leveraging work already being performed during system synthesis and DT development is pushed earlier in a system's lifecycle. This article contributes to the definition and development processes for DTs by proposing a DT development model and path, a method for scoping and defining requirements for a DT, and an approach to integrate DT and system development. An example case study of a Naval unmanned system is presented to illustrate the contributions.