Product Release Time Research Articles

Software Reliability Growth Models with Exponentiated-gompertz Testing Effort and Release Time Determination

Quality is a consequential factor for the software product. During the software development at most care was taken at each step for the quality product. Development process generally embedded with several qualitative and quantitative techniques. The characteristics of final software product should reach all the standards. Reliability is a paramount element which quantifications the probability that a software product could able to work afore it authentically fails to perform its intended functionality. Software testing is paramount phase where gargantuan resources were consumed. Over around fifty percent of cost was consumed during this testing phase, that is why testing was performed in disciplined environment. Software product release time is considered to be crucial subject at which the software product testing was stopped and it could be release into market, such that the software product should have quality and reliability. In this paper we have investigated the concept of software testing effort dependent software reliability growth models by considering the exponentiated-gompertz function as testing effort function to determine the release time of the software. Thus, constructed testing effort dependent models was computed on three authentic time datasets. Parameter estimation is done through least square estimation and metrics like Mean square Error (MSE) and Absolute Error (AE) are utilized for model comparison. The proposed testing effort dependent model performance was better than the rest of the models.

Optimal product release time for a new high-tech startup firm under technical uncertainty

<p style='text-indent:20px;'>Decision makers of new high-tech startup firms always want to choose an optimal time to launch their products which are under research and development (R&D) to obtain the maximum net income of these firms. However, existing models fail to consider the optimal release time of products for these new high-tech startup firms. In this paper, the optimal time to launch the product of the R&D project is assumed to be the first time when the product of the R&D project is released to the market. Based on this assumption, we develop a continuous-time model to find the optimal time at which the startup firm launches its product of the R&D project by considering the price of the similar product. Employing the methods of dynamic programming and variational inequalities, we also provide a closed form solution to our model. We also find that these high-tech startup firms prefer to delay their product release time when the price of the similar product is at a phase of rapid growth or the price has considerable uncertainty. Moreover, some numerical examples are provided to investigate the properties of our model.</p>

AmyJ33, a truncated amylase with improved catalytic properties

Biochemical and kinetic properties are of special interest for the specific applications of α-amylases in industrial sectors such as textile industries, detergents, biofuels and food among others. Therefore, protein engineering is currently directed towards a continuous demand to improve the properties of amylases and thus meet the specific characteristics for various industrial sectors. In the present work, modular protein engineering was performed to improve the biochemical and kinetic properties of AmyJ33r an α-amylase isolated from Bacillus siamensis JJC33M consisting of five domains, A, B, C, D and E (SBD) (Montor-Antonio et al. in 3 Biotech 7:336, 2017. https://doi.org/10.1007/s13205-017-0954-8 ). AmyJ33r is not active on native starch, only showing activity on gelatinized starch. At the C-terminal, AmyJ33r has a starch binding domain (SBD, domain E) belonging to the CBM26 family. In this study, four truncated versions were constructed and expressed in E. coli (AmyJ33-AB, AmyJ33-ABC, AmyJ33-ABCD, and SBD) to determine the role of the A, B, C, D, and E domains in the biochemical behavior of AmyJ33r on starch. Biochemical and kinetic characterization of the truncated versions showed that domain C is essential for catalysis; domain D improved enzyme activity at alkaline pH values, is also involved negatively in thermostability at 40, 50, and 60°C and its presence favored the production of maltooligosaccharides with a higher degree of polymerization (DP4). E domain have interaction with raw starch, also the deletion of E domain (SBD) favors the affinity for the substrate while the deletion of D domain increased enzyme kcat at the time of product release. In conclusion, AmyJ33-ABC has better kinetic parameters than AmyJ33-ABCD and AmyJ33r, but is less stable than these two enzymes.

Drying methods of the printing inks

Accelerating the transition to post-print processes needed in the printing industry and shortening the time the product's release time is closely related to the drying time of the ink film. The drying of fluid ink on the surface of the print substrate, transforming from liquid to solid occurs physically and chemically in several ways. Drying systems can be functional alone on the surface of the printing substrate for an ink film or depending on the chemical content of the ink and the properties of the printing substrate, drying can be achieved at the same time with more than one system.Recently, in order to reduce climate, environmental and health impacts and with the development of technology, significant changes are also being experienced in the printing industry and preferences are changing. In this study, more environmentally friendly LED UV and microwave drying systems that save time and energy together with existing basic drying systems such as absorption, evaporation, oxidation-polymerization and conventional UV used in the printing industry are examined. The advantages of different drying systems to the printing industry, preferred drying systems and new studies on this issue have been evaluated.

A joint modeling approach for reliability growth planning considering product life cycle cost performance

Reliability growth planning methods have been traditionally focusing on the product design stage rather than the product whole life cycle including both product development and deployment stages. A joint modeling approach for reliability growth planning considering product life cycle cost performance is proposed. The product life cycle performance consists of the cost of reliability growth test, early release incentive or late release penalty, and after sales maintenance cost. The product early release incentive or late release penalty is a virtual cost, which quantifies the impact of product release timing on the product life cycle cost assessment. The reliability growth test cost depends on the allocated testing units and times, which consequently determines the reliability level at product release time and the subsequent maintenance cost. The proposed joint modeling approach balances and determines the optimal product release time and reliability growth test resource allocation with the objective of minimizing the product life cycle cost. A numerical example is illustrated to demonstrate the advantages of the proposed method over traditional reliability growth planning approaches.

Power Flow Simulation in the Product Development Process of Modern Vehicular DC Distribution Systems

Nowadays, automakers face unprecedented requirements to comply and exceed quality standards while attending to consumer expectations. Among the challenges are the insertion of new functions for driving assistance towards highly automated vehicles, electrification and connectivity. Introduction of simulation – driven design in the broad wide disciplines involved within vehicles development yields significant savings in both costs and product release time. This paper introduces an approach to vehicle electrical distribution systems (EDS) simulation adapting the methods used conventionally in transmission and distribution systems to the special features found in the vehicle EDS. To this purpose, a procedure based on a backward/forward sweep (BFS) algorithm for solving power flows in weakly meshed dc traction networks is applied and described. An important part of the work has to do with the information pre-processing from the modular based format used in automotive industry into standard simulation matrices. Constant current load profiles are assumed for the consumers, while the electronic control units (ECU) are considered static power distribution boxes. The main outputs of the proposed methodology are nodal voltages, branch currents and differential voltages at components terminals in the vehicle EDS. The knowledge extracted from the simulation will help the designers during the dimensioning and validation process of modern vehicles EDS and will be a powerful tool to reach the zero-prototypes goal before the start of production.

Optimal Release Time Determination in Intuitionistic Fuzzy Environment Involving Randomized Cost Budget for SDE-Based Software Reliability Growth Model

To enhance the accuracy of estimating the reliability of the software, it becomes essential to count upon the proportion of faults that are predominantly dormant due to fault masking. In addition to that, the software managers and developers primarily aim at obtaining the date of product release by attaining a compromise between maximizing the reliability level and minimizing the product development cost. Keeping in mind the above requirements for reliability estimation, a stochastic differential equation-based software reliability growth model (SRGM) is developed for open-source software. Multi-release of the SRGM is formulated in detail taking into consideration the effect of bug classification. An innovative safe technique called Rx is deployed which is capable of recovering programs from both deterministic and indeterministic bugs. The optimal date of product release is obtained via a parabolic multi-objective chance-constrained nonlinear optimization problem in the parabolic intuitionistic fuzzy set environment. The optimization model framed to determine the time of product release is critically analyzed from both optimistic and pessimistic viewpoints of the developer. The results manifest the better performance of the model proposed in comparison with some preexisting SRGMs reported in the literature. Moreover, the exemplified methodology corresponding to the attainment of the optimal date for product release is well established as it is truly capable of taking into consideration, the level of tolerance of the developer pertaining to variations in both reliability and cost.

Optimal Release Time Determination Using FMOCCP Involving Randomized Cost Budget for FSDE-Based Software Reliability Growth Model

This paper presents a software reliability growth model (SRGM) based on a fuzzy stochastic differential equation (FSDE) approach. The software shall comprise of dependent and independent main and sub-components owing to a wide range of functionalities in the system. In order to obtain the optimal date of product release, a two-phase fuzzy goal programing (FGP) method has been applied for solving a fuzzy multi-objective chance-constrained programming (FMOCCP) model. While framing the cost function, the costs associated with changes in software specifications have been considered along with other cost factors. In most cases, the changes in software specifications during the software development process are dynamic in nature necessitating the cost budget to be considered as a random variable while formulating the fuzzy chance-constrained model. The SRGM proposed has been validated on real-time data sets and numerical illustrations have been provided to instantiate the optimal time of product release.

A Study on the Diagnostic Method of Lineup Flow and Core Design Area to Secure Design Identity

Background : This study explores a strategic diagonal way to secure design identity from a homogeneity and continuity context. Therefore, the forehead part of a high-speed train was selected as the subject of this homogeneity experiment shape and longer life span. In addition, we analyzed the trend of lineup models from the initially-released prototype to more recent models. The outcomes are illustrated in a diagram as a 3-dimensional structure that is capable of diagnosing the design identity. Methods : We organized the discussion on design identity and developed a research model in consideration of homogeneity and continuity based on existing studies. Specifically, we surveyed researchers in the design sector and examined quantitative data extraction. We also applied a homogeneity analysis, through multi-dimensional scaling. In addition, we investigated the point of product release time, applied a 2-dimensional positioning map, and examined a final lineup flow and routes. Results : We analyzed and schematized the homogeneity analysis and lineup model flow to show the design identity diagonal process. First, based on the homogeneity analysis, we schematized the core design area. Second, we found that by centering on the initially-released prototype, with time, the lineup flow formed in a spiral shape. We estimated that such a flow signals and that the released models changed continuously in a gradual manner while they maintained homogeneity on the initial model. Conclusion : The discussion above is organized by identifying the core design areas in the homogeneity aspect. The 3-dimensional flow in the continuity aspect also can serve as a strategic foundation to diagnose the company’s lineup flow and deviation models. In addition, the findings are highly applicable as a strategic diagonal method to secure design identity of high-speed trains and other products. Furthermore, the findings can be utilized as a professional approach for design identity and lineup diagnosis in relation to other competing companies.

Aluminum in Pediatric Parenteral Nutrition Products: Measured Versus Labeled Content

Aluminum is a contaminant in all parenteral nutrition solutions. Manufacturers currently label these products with the maximum aluminum content at the time of expiry, but there are no published data to establish the actual measured concentration of aluminum in parenteral nutrition solution products prior to being compounded in the clinical setting. This investigation assessed quantitative aluminum content of products commonly used in the formulation of parenteral nutrition solutions. The objective of this study is to determine the best products to be used when compounding parenteral nutrition solutions (i.e., those with the least amount of aluminum contamination). All products available in the United States from all manufacturers used in the production of parenteral nutrition solutions were identified and collected. Three lots were collected for each identified product. Samples were quantitatively analyzed by Mayo Laboratories. These measured concentrations were then compared to the manufacturers' labeled concentration. Large lot-to-lot and manufacturer-to-manufacturer differences were noted for all products. Measured aluminum concentrations were less than manufacturer-labeled values for all products. The actual aluminum concentrations of all the parenteral nutrition solutions were significantly less than the aluminum content based on manufacturers' labels. These findings indicate that 1) the manufacturers should label their products with actual aluminum content at the time of product release rather than at the time of expiry, 2) that there are manufacturers whose products provide significantly less aluminum contamination than others, and 3) pharmacists can select products with the lowest amounts of aluminum contamination and reduce the aluminum exposure in their patients.

Aluminum Content of Parenteral Nutrition in Neonates: Measured Versus Calculated Levels

Aluminum (Al) is associated with significant central nervous system toxicity and bone and liver damage. Because Al is a contaminant of parenteral nutrition (PN) components including calcium and phosphate additives, premature infants are at potentially high risk for toxicity. The US Food and Drug Administration (FDA) has mandated PN component product labeling and recommended maximum Al daily exposure limits. The objective of this article is to determine the actual Al content of neonatal PN solutions, compare these values to the calculated amounts from manufacturers' PN product labels, and ascertain whether the actual Al exposure exceeds the FDA recommended maximum of 5 microg . kg(-1) . day(-1). Samples from 40 neonatal patient PN solutions were selected for sampling and Al content determination. Samples were also taken from 16 manufacturer's component products used in PN formulation. All of the samples were sent to Mayo Laboratories for Al content measurement. The calculated Al concentrations in PN samples were determined from the manufacturer's labeled content. Both measured and calculated Al concentrations exceeded the FDA recommended safe limit of <5 microg . kg(-1) . day(-1). The actual measured Al content was significantly lower than the calculated Al content in both the patient PN solutions and the component product samples. Al exposure exceeded the FDA recommended maximum limit for all patient samples; however, the actual measured Al content of all the samples was significantly less than the calculated Al content based on manufacturer's labels. These findings suggest that manufacturers label their products with actual Al content at the time of product release rather than at time of expiration. Periodic monitoring of Al levels should be considered with prolonged PN therapy. Changes in manufacturing processes, including the use of better raw materials, are essential to reduce Al contamination to meet FDA mandates.

Total System Reliability: Integrated Model for Growth and Test Termination

Reliability demonstration testing is not the most efficient method of assuring product reliability prior to shipment. It is costly, time consuming and has inherent technical and social limitations. The dilemma facing the reliability and quality engineer is whether to continue demonstration testing and risk shipping a product late or ship the product and risk warranty and field service returns. Either option can cause the company to lose significant market share and profit. This paper sets out to solve this dilemma by meeting both the time to market constraints and the product reliability goals. The weaknesses of existing reliability demonstration techniques are explored and a comprehensive methodology is introduced involving controlled development processes, stress testing, root cause determination and process change feedback mechanisms. All prototype products are manufactured on the final volume process line resulting in the early identification and correction of process-related problems. Testing commences on the first available prototypes with system stress/robust testing being employed to stimulate failures, determine their root cause and correct them. Reliability growth modelling assesses the ongoing improvements occurring in reliability during the development cycle, while a statistical stopping rule is used to determine the optimal product release time without risking product warranty. The approach is applicable to systems incorporating both hardware and software elements. The methodology has been validated on three development projects of telecommunication systems comprising hardware and software. In addition to enhancing team behaviour and performance, the development times have been reduced by 14% and the ramp-up time to full worldwide product shipments has been reduced by 50%. Copyright © 2005 John Wiley & Sons, Ltd.

Organizing product releases in time-driven development processes: a probabilistic analysis

In this paper, the problem is addressed of how to organize a new product development process that is fast on the one hand and that provides good-quality results on the other hand. Several planning techniques, like PERT and CPM, are available to analyse the completion time or product release time of such complex processes. Although these techniques are all well known and are widely used in project management, they do not address the iterative mode of operation that is characteristic for such uncertain processes. Neither do they offer a tool or guidelines to ‘design’ a composition of iterative processes because they are analytical. In this paper, a quantitative concept is presented for modelling the release time of a single uncertain iterative activity, as a random variable to deal with the probabilistic aspect in a simple way. From this simple model, the complexity is extended systematically to model fundamentally different configurations, that are on the one hand simple enough to be studied analytically and on the other hand exhibit their fundamentally different release characteristics, as experienced in real life. From the analysis, guidelines are formulated for organizing or (re)configuring a complex process configuration. It is demonstrated that organizing uncertain processes for a fast product release requires a balance between the exploitation of the principles of concurrent engineering and the risk of overrunning time targets. An important factor in this balance is the decision structure for the release of intermediate results. The ‘empowerment’ structure, a structure where decisions are not clustered as milestones but are made without any delay, offers great opportunity in terms of small mean release times and small variances thereof.

A Risk Index for Software Producers

Software risk management has been receiving increasing attention lately. A key activity of software risk management is the quantification of the risk of using a software product. Previous attempts to define the risk index have taken the users' viewpoint. The loss due to a product failure is computed based on its impact on the users. Yet, the impact of a failure on the software producer is different from that of the users. A high risk module according to the users may not be treated the same by the producer. This paper presents a method to determine the producer risk index for quantifying the probability and impact of failure on the producer at the product release time. The producer can use the results to determine whether it is more economical to improve the software quality or to release the product with the achieved quality level. The index can also be used to estimate the maintenance effort. The approach makes use of two recent developments in software complexity metrics, principal component analysis and reliability growth modelling. A new classification scheme for failure impact is introduced. Results from applying the producer risk index to a telecommunication software system are presented.