Implementasi Metode Overall Equipment Effectiveness Berbasis Six Big Losses Guna Mengevaluasi Efektivitas Mesin Packing Semen

Integrated maintenance management is an important factor in maintaining the stability of machine operations in manufacturing companies. PT AAAA Factory Gresik is a cement manufacturing company, where the Section Division of Gresik Finish Mill Packer Operation has a problem of downtime cement packing machine 40 kg and causes production delay. This study aims to evaluate the effectiveness of the 40kg cement packing machine as well as to calculate losses due to unproductiveness of the packing machine. Overall Equipment Effectiveness (OEE), Six Big Losses, and Failure Mode and Effect Analysis (FMEA) were used as research method. This study found that OEE value for January-December 2019 of 41.25% are considered as lower percentage in compare with the ideal value of international standards which is 85%. Moreover, the largest average losses are found, namely reduce speed losses, idle and stoppages minor losses and defects in process with percentage in following order, 4.49%, 4.49% and 2.76%.Result from FMEA analysis have been identified 3 highest Risk Priority Number (RPN), namely transportation with an RPN value of 294, the second RPN value of 288 is a blockage in the packing machine, finally the engine button is jammed with an RPN value of 252. The proposed improvement scenario is the start of the engine operating operators checking and cleaning machines regularly and the marketing division expands the sales market.

Mixture distributions in a stochastic gene expression model with delayed feedback

Noise in gene expression can be substantively affected by the presence of production delay. Here we consider a mathematical model with bursty production of protein, a one-step production delay (the passage of which activates the protein), and feedback in the frequency of bursts. We specifically focus on examining the steady-state behaviour of the model in the slow-activation (i.e. large-delay) regime. Using a quasi-steady-state (QSS) approximation, we derive an autonomous ordinary differential equation for the inactive protein that applies in the slow-activation regime. If the differential equation is monostable, the steady-state distribution of the inactive (active) protein is approximated by a single Gaussian (Poisson) mode located at the globally stable steady state of the differential equation. If the differential equation is bistable (due to cooperative positive feedback), the steady-state distribution of the inactive (active) protein is approximated by a mixture of Gaussian (Poisson) modes located at the stable steady states; the weights of the modes are determined from a WKB approximation to the stationary distribution. The asymptotic results are compared to numerical solutions of the chemical master equation.

Genome-wide modeling of transcription kinetics reveals patterns of RNA production delays

Genes with similar transcriptional activation kinetics can display very different temporal mRNA profiles because of differences in transcription time, degradation rate, and RNA-processing kinetics. Recent studies have shown that a splicing-associated RNA production delay can be significant. To investigate this issue more generally, it is useful to develop methods applicable to genome-wide datasets. We introduce a joint model of transcriptional activation and mRNA accumulation that can be used for inference of transcription rate, RNA production delay, and degradation rate given data from high-throughput sequencing time course experiments. We combine a mechanistic differential equation model with a nonparametric statistical modeling approach allowing us to capture a broad range of activation kinetics, and we use Bayesian parameter estimation to quantify the uncertainty in estimates of the kinetic parameters. We apply the model to data from estrogen receptor α activation in the MCF-7 breast cancer cell line. We use RNA polymerase II ChIP-Seq time course data to characterize transcriptional activation and mRNA-Seq time course data to quantify mature transcripts. We find that 11% of genes with a good signal in the data display a delay of more than 20 min between completing transcription and mature mRNA production. The genes displaying these long delays are significantly more likely to be short. We also find a statistical association between high delay and late intron retention in pre-mRNA data, indicating significant splicing-associated production delays in many genes.

A state-space model of a three tier APVIOBPCS supply chain

Purpose – The purpose of this paper is to investigate a control engineering-based system model that allows for any value of production delay for a three-tier supply chain with information delays between tiers or systems with epos. Design/methodology/approach – A discrete z transform model of automatic pipeline, variable inventory and order based production control system three-tier supply chain is obtained using a state-space model using a reachable control formulation. This model provides a discrete time state-space model conversion using an exponential production delay with no loss of generality. Findings – This work allows a three-tier supply chain model to be computed via a spreadsheet using any production delay and can be modified to include different sales smoothing procedures. The model is fully controllable and observable. Stability of these models is obtained from the system eigenvalues and agrees with our previously published stability boundaries. Practical implications – The system is described by a linear control model of the production process and does not include production limits or other resource limitations, including history of sales demand and response. Originality/value – This present model is an extension of the model devised by White and Censlive, in that it allows accurate modelling of multi-tier inventory production systems by permitting flexible selection of delay parameter values for real systems.

Effect of 1-Methylcyclopropene Treatment on the Quality of Rape (Brassica campestris L.) during Cold Storage

Taking ‘HuaGuan’ Rape as material, studied the effect of 1-methylcylopropene treatments on postharvest quality of rape stored under 0 °C. The results indicated that during the storage 1-MCP treatment could inhibit the ethylene production, delay the ethylene peak and the color of rape changed from green to yellow, keep the weight, maintain the good appearance quality of rape.

PERANCANGAN APLIKASI e-SCM PADA PT CAHAYA BUANA FURINDOTAMA

PT Cahaya Buana Furindotama is a company incorporated in the Olympic Group. This company is a manufacturingcompany which produces furniture and household-wares made from plastic material. Problems en countered were rawmaterial shortage and production delay, though the company already had a partnership with several suppliers because ofthe un-integrated data and there was a “human error” in data entry. Results of the problem were the company could losemarket share and threatened with competitors’ position. Based on the problems which arose, it was proposed to use an e-SCMapplication system at the company because e-SCM application system could help the company to manage flow of raw materialbetter and strengthen the company’s relationship between suppliers and distributors. The methods used were Porter’s FiveForces to analyze the company’s position in market and SWOT Method to determine a strategy could be used by the company.Based on the internal matrix (IFE), the result obtained was 3:08. Whereas, the external matrix (EFE), the result obtained was3:34. Based on both results, it can be concluded that the company is in a strong position in matrix IE. Whereas, the strategyused is Strengths-Opportunity (SO) which is in SWOT matrix. It is expected that the SO strategy and e-SCM applicationsystem, the company can be more strength its position in the market.Keywords: e-SCM, SWOT, internal matrix, external matrix