The Role of Lean and Agile Logistics during Production Ramp-Up

In addition to the rareness of theoretical and empirical research, which extends to every aspect of the production ramp-up literature, the increasing importance of the ramp-up phase – due to the continuously decreasing product lifecycle in almost all industrial sectors –magnifies the need for more research efforts in this field. Based on a comprehensive literature review, no attempts to investigate the role of lean and/or agile logistics during the ramp-up stage were found. Utilizing the survey method, this research empirically explores the effects of lean and agile logistics on production performance during the ramp-up phase in terms of quantity, quality, and cost. A special purpose questionnaire was developed to collect primary data based on a literature review in the fields of production ramp-up, lean logistics, lean production, agile logistics, agile production, performance measurement, and product success. The measurement model was evaluated for validity and reliability and tested for temporal consistency and the existence of common method variance; the collected data were tested for measurement and non-response biases; and the results were evaluated for their statistical power and statistical conclusion error. Out of 63 questionnaires collected from industrial organizations operating in 7 countries and in different sectors, 56 responses were used in the statistical analyses. A two-step methodological approach was utilized in the data analysis. In the first step, the data collected on the research variables were analysed following a theory confirmation procedure to examine the validity of a hypothesized positive effect of lean and agile logistics on ramp-up performance. In addition, the effect of ramp-up performance on new products’ success, the moderating effect of some respondent, organizational, and product-related variables, and the mediating effect of outbound logistics were investigated. The partial least squares method of structural equation modelling (PLS-SEM) was employed during the confirmatory analysis. Different scenarios were evaluated to test the main and subsidiary hypotheses proposed, based on the use of formative and reflective measures and first- or higher-order variable formats. The results of the confirmatory data analysis supported the hypothesized positive effect of lean and agile logistics on production performance during the ramp-up phase. In the second methodological step, exploratory analyses were conducted to explore further patterns in the data collected. Correlation matrices indicated a greater effect of agility on quantity performance and a greater effect of leanness on cost performance. Such trends are generally accepted and supported by the theoretical literature and by practitioners. However, the agreed-upon priorities of time reduction during the ramp-up phase and cost reduction during the steady-state and ramp-down phases motivated the proposition of a mixed model that uses higher levels of agility throughout the ramp-up phase and higher leanness levels thereafter. The proposed mixed system was supposed to outperform the pure lean, pure agile, and leagile strategies. Among the methods proposed to apply such a mixed production system, the development of a specialized agile ramp-up facility was introduced. It was suggested that all products undergoing a ramp-up phase should be produced with an agile system, in a specialized ramp-up facility, and then moved to a lean facility during the steady-state and ramp-down production phases. To examine the feasibility of the proposed system and the magnitude of investment that might be accepted to gain the expected enhancement, the total lifecycle profitability of each system – lean, agile, leagile, and mixed – was calculated and compared to provide insights into the advantages of the mixed system and the conditions that increase or decrease the appeal of investing in such a strategy. It was concluded that the adoption of the proposed system and the asset investment magnitude should be evaluated considering different possible combinations of the product’s type, price, cost, contribution, and lifecycle length, among other variables. The proposed system has been proven to be more attractive to adopt as the proportion of the ramp-up time to the total lifecycle increases, as the product’s price drops faster, as the peak sales are reached earlier, or as the number of ramp-ups increases

The development of a radial based integrated network for the modelling of 3D fused deposition

Purpose The purpose of this research paper is to investigate and model the fused deposition modelling (FDM) process to predict the mechanical attributes of 3D printed specimens. Design/methodology/approach By exploiting the main effect plots, a Taguchi L18 orthogonal array is used to investigate the effects of such parameters on three mechanical attributes of the 3D printed specimens. A radial-based integrated network is then developed to map the eight FDM parameters to the three mechanical attributes for both PEEK and PEKK. Such an integrated network maps and predicts the mechanical attributes through two consecutive phases that consist of several radial basis functions (RBFs). Findings Validated on a set of further experiments, the integrated network was successful in predicting the mechanical attributes of the 3D printed specimens. It also outperformed the well-known RBF network with an overall improvement of 24% in the coefficient of determination. The integrated network is also further validated by predicting the mechanical attributes of a medical-surgical implant (i.e. the MidFace Rim) as an application. Originality/value The main aim of this paper is to accurately predict the mechanical properties of parts produced using the FDM process. Such an aim requires modelling a highly dimensional space to represent highly nonlinear relationships. Therefore, a radial-based integrated network based on the combination of composition and superposition of radial functions is developed to model FDM using a limited number of data points

Fuzzy particle swarm for the right-first-time of fused deposition

Right-first-time production enables manufacturing companies to be profitable as well as competitive. Ascertaining such a concept is not as straightforward as it may seem in many industries, including 3D printing. Therefore, in this research paper, a right-first-time framework based on the integration of fuzzy logic and multi-objective swarm optimization is proposed to reverse-engineer the radial based integrated network. Such a framework was elicited to represent the fused deposition modelling (FDM) process. Such a framework aims to identify the optimal FDM parameters that should be used to produce a 3D printed specimen with the desired mechanical characteristics right from the first time. The proposed right-first-time framework can determine the optimal set of the FDM parameters that should be used to 3D print parts with the required characteristics. It has been proven that the right-first-time model developed in this paper has the ability to identify the optimal set of parameters successfully with an average error percentage of 4.7%. Such a framework is validated in a real medical case by producing three different medical implants with the desired mechanical characteristics for a 21-year-old patient

SARS-CoV-2 viral RNA shedding for more than 87 days in an individual with an impaired CD8+ T cell response

Prolonged shedding of viral RNA occurs in some individuals following SARS-CoV-2 infection. We perform comprehensive immunologic evaluation of one individual with prolonged shedding. The case subject recovered from severe COVID-19 and tested positive for SARS-CoV-2 viral RNA repeatedly as many as 87 days after the first positive test, 97 days after symptom onset. The subject did not have any associated rise in anti-Spike protein antibody titers or plasma neutralization activity, arguing against re-infection. This index subject exhibited a profoundly diminished circulating CD8+ T cell population and correspondingly low SARS-CoV-2-specific CD8+ T cell responses when compared with a cohort of other recovering COVID-19 subjects. CD4+ T cell responses and neutralizing antibody responses developed as expected in this individual. Our results demonstrate that detectable viral RNA shedding in the upper airway can occur more than 3 months following infection in some individuals with COVID-19 and suggest that impaired CD8+ T cells may play a role in prolonged viral RNA shedding

Extremely potent human monoclonal antibodies from COVID-19 convalescent patients

Human monoclonal antibodies are safe, preventive and therapeutic tools, that can be rapidly developed to help restore the massive health and economic disruption caused by the coronavirus disease 2019 (COVID-19) pandemic. By single cell sorting 4,277 SARS-CoV-2 spike protein specific memory B cells from 14 COVID-19 survivors, 453 neutralizing antibodies were identified. The most potent neutralizing antibodies recognized the spike protein receptor binding domain, followed in potency by antibodies that recognize the S1 domain, the spike protein trimer and the S2 subunit. Only 1.4% of them neutralized the authentic virus with a potency of 1-10 ng/mL. The most potent monoclonal antibody, engineered to reduce the risk of antibody dependent enhancement and prolong half-life, neutralized the authentic wild type virus and emerging variants containing D614G, E484K and N501Y substitutions. Prophylactic and therapeutic efficacy in the hamster model was observed at 0.25 and 4 mg/kg respectively in absence of Fc-functions