Learning from Post-project Reviews : A Cross-Case Analysis

Every new product development (NPD) project should not only deliver a successful new product but also should generate learning for the organization. Postproject reviews (PPRs) are recognized by both practitioners and academics as an appropriate mechanism to stimulate and capture learning in NPD teams. However, relatively few companies use PPRs, and those that do use them often fail to do so effectively. Although they are widely perceived to be a useful tool, empirical research on how PPRs are typically organized and the learning that results is limited. The present article addresses this gap in the extant knowledge and describes five in-depth case studies, which were conducted at leading companies in Germany. A detailed investigation was made of how PPRs are conducted and of the type of learning that can result. Three main sources of data were used for each case: company documentation, in-depth interviews with managers responsible for NPD, and observation of an actual PPR. The different data sources enabled extensive triangulation of data to be conducted and a high degree of reliability and validity to be achieved. The analysis enabled a number of key characteristics of the way PPRs are managed to be identified. Various characteristics of PPRs influence their utility, such as the time at which they take place and the way discussions are moderated. In addition, the data show that participants in the discussions at PPRs often use metaphors and stories, which indicates that PPRs have the potential to generate tacit knowledge. Interestingly, the data also show that there are various different ways in which metaphors and stories appear to stimulate discussions on NPD projects. Based on the cross-case analysis, a wide range of implications are identified. Researchers need to investigate PPRs further to identify how they can generate tacit and explicit knowledge and support project-to-project learning. The generation of tacit knowledge in NPD is a topic that particularly needs further investigation. The research also led to a range of recommendations for practitioners. Companies need to strongly communicate the purpose and value of PPRs, to run them effectively to stimulate the maximum possible learning, and to disseminate the findings widely. PPRs have the potential to create and transfer knowledge amongst NPD professionals, but, as they are seldom currently used, many companies are missing an important opportunity

A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution

We describe a method to obtain point and dispersion estimates for the energies of jets arising from b quarks produced in proton–proton collisions at an energy of s=13TeV at the CERN LHC. The algorithm is trained on a large sample of simulated b jets and validated on data recorded by the CMS detector in 2017 corresponding to an integrated luminosity of 41 fb-1. A multivariate regression algorithm based on a deep feed-forward neural network employs jet composition and shape information, and the properties of reconstructed secondary vertices associated with the jet. The results of the algorithm are used to improve the sensitivity of analyses that make use of b jets in the final state, such as the observation of Higgs boson decay to b b ¯. © 2020, The Author(s)

Measurement of single-diffractive dijet production in proton–proton collisions at √s=8Te with the CMS and TOTEM experiments

Measurements are presented of the single-diffractive dijet cross section and the diffractive cross section as a function of the proton fractional momentum loss ξ and the four-momentum transfer squared t. Both processes pp→pX and pp→Xp, i.e. with the proton scattering to either side of the interaction point, are measured, where X includes at least two jets; the results of the two processes are averaged. The analyses are based on data collected simultaneously with the CMS and TOTEM detectors at the LHC in proton–proton collisions at s=8Te during a dedicated run with β∗=90m at low instantaneous luminosity and correspond to an integrated luminosity of 37.5nb-1. The single-diffractive dijet cross section σjjpX, in the kinematic region ξ< 0.1 , 0.03<|t|<1Ge2, with at least two jets with transverse momentum pT>40Ge, and pseudorapidity | η| < 4.4 , is 21.7±0.9(stat)-3.3+3.0(syst)±0.9(lumi)nb. The ratio of the single-diffractive to inclusive dijet yields, normalised per unit of ξ, is presented as a function of x, the longitudinal momentum fraction of the proton carried by the struck parton. The ratio in the kinematic region defined above, for x values in the range - 2.9 ≤ log 10x≤ - 1.6 , is R=(σjjpX/Δξ)/σjj=0.025±0.001(stat)±0.003(syst), where σjjpX and σjj are the single-diffractive and inclusive dijet cross sections, respectively. The results are compared with predictions from models of diffractive and nondiffractive interactions. Monte Carlo predictions based on the HERA diffractive parton distribution functions agree well with the data when corrected for the effect of soft rescattering between the spectator partons. © 2020, CERN for the benefit of the CMS and TOTEM collaborations

Measurements of triple-differential cross sections for inclusive isolated-photon+jet events in p p collisions at √s=8TeV

Measurements are presented of the triple-differential cross section for inclusive isolated-photon+jet events in p p collisions at s=8 TeV as a function of photon transverse momentum (pTγ), photon pseudorapidity (ηγ), and jet pseudorapidity (ηjet). The data correspond to an integrated luminosity of 19.7fb-1 that probe a broad range of the available phase space, for | ηγ| < 1.44 and 1.57 < | ηγ| < 2.50 , | ηjet| < 2.5 , 40<pTγ<1000GeV, and jet transverse momentum, pTjet, > 25GeV. The measurements are compared to next-to-leading order perturbative quantum chromodynamics calculations, which reproduce the data within uncertainties. © 2019, CERN for the benefit of the CMS collaboration

Measurements with silicon photomultipliers of dose-rate effects in the radiation damage of plastic scintillator tiles in the CMS hadron endcap calorimeter

Measurements are presented of the reduction of signal output due to radiation damage for two types of plastic scintillator tiles used in the hadron endcap (HE) calorimeter of the CMS detector. The tiles were exposed to particles produced in proton-proton (pp) collisions at the CERN LHC with a center-of-mass energy of 13 TeV, corresponding to a delivered luminosity of 50 fb-1. The measurements are based on readout channels of the HE that were instrumented with silicon photomultipliers, and are derived using data from several sources: A laser calibration system, a movable radioactive source, as well as hadrons and muons produced in pp collisions. Results from several irradiation campaigns using 60Co sources are also discussed. The damage is presented as a function of dose rate. Within the range of these measurements, for a fixed dose the damage increases with decreasing dose rate

Azimuthal separation in nearly back-to-back jet topologies in inclusive 2- and 3-jet events in pp collisions at √s=13Te

A measurement for inclusive 2- and 3-jet events of the azimuthal correlation between the two jets with the largest transverse momenta, Δϕ12, is presented. The measurement considers events where the two leading jets are nearly collinear (“back-to-back”) in the transverse plane and is performed for several ranges of the leading jet transverse momentum. Proton-proton collision data collected with the CMS experiment at a center-of-mass energy of 13Te and corresponding to an integrated luminosity of 35.9fb-1 are used. Predictions based on calculations using matrix elements at leading-order and next-to-leading-order accuracy in perturbative quantum chromodynamics supplemented with leading-log parton showers and hadronization are generally in agreement with the measurements. Discrepancies between the measurement and theoretical predictions are as large as 15%, mainly in the region 177 ∘< Δϕ12< 180 ∘. The 2- and 3-jet measurements are not simultaneously described by any of models. © 2019, CERN for the benefit of the CMS collaboration