Product Performance Levels Research Articles

Digital Twins for Smart Home Gadget Threat Prediction using Deep Convolution Neural Network

Digital twin is one of the most important innovations in the Internet of Things (IoT) era and business disruption. Digital twins are a growing technology that bridges the gap between the real and the digital. Home automation in the IoT refers to the practice of automatically managing and monitoring smart home electronics by use of a variety of control system methods. The geysers, refrigerators, fans, lighting, fire alarms, kitchen timers, and other electrical and electronic items in the home can all be managed and monitored with the help of a variety of control methods. Digital twins replicate the physical machine in real time and produce data, such as asset degradation, product performance level that may be used by the predictive maintenance algorithm to identify the product functionality levels. The purpose of this research is to design the framework of Digital Twin using machine learning and state estimation algorithms model to assess and predict home appliances based on the probability rate of smart home system gadgets functionality. The main goal of this research is to create a digital twin for smart home gadgets that are used to monitor the health status of these devices for increasing the life time and to reduce maintenance costs. This research presents a Deep Convolution Neural Network based Logistic Regression Model with Digital Twins (DCNN-LR-DT) for accurate prediction of smart home gadget functionality levels and to predict the threats in advance. The proposed model is compared with the traditional models and the results represent that the proposed model performance is better than traditional models.

Dynamic assignment of a multi-skilled workforce in job shops: An approximate dynamic programming approach

We propose an approximate algorithm to dynamically assign a multi-skilled workforce to the stations of a job shop, with demand uncertainty and variability in the availability of the resources, to maximize productivity.Our proposed model is inspired by automotive glass manufacturing, where maximizing the surface area of manufactured safety glass during a given time frame is the key performance measure. We first develop the model of a traditional job shop with a set of stations, each with a particular number of machines, with distinct production performance levels, according to their utilization stage. Each product type needs to be processed on a subset of these stations according to a predefined sequence. Customers place their orders independently over time, specifying the units required of each product type. The inter-arrival of orders (demand) and processing times are assumed to be stochastic. We also suppose that the technicians have varied skill sets, according to which they can only work at a certain subgroup of stations, and variable availability depending on sick leave, vacations, etc. Hence, in order to maximize the predefined productivity index, the optimal assignment of technicians to the stations based on their skill sets and availability during each shift becomes a complex decision-making process.Given the stochastic and dynamic nature of this problem, we model the setting as a Markov Decision Process (MDP). Given its size, we propose to solve it using Approximate Dynamic Programming (ADP). We address the exponential growth of the action space by using a hill-climbing algorithm for action selection. To show the performance and effectiveness of the proposed algorithm, we use real company data and compare the results of the algorithm with the current policy in use, as well as other proposed policies. Applying our proposed method resulted in an average improvement of 15% in productivity compared to the best performing benchmark policy.

Key Approaches, Risks, and Product Performance in Managing the Development Process of Complex Products Sustainably

In the Industry 4.0 environment, being sustainably competitive is essential in global markets. In an endeavor to optimize the added value in the design process of complex products such as robots, managing the development process of such products is studied. The present study identifies the level of product performance that yields maximum return on product development in Industry 4.0. The study also identifies and reviews the key approaches to understanding and managing the design process of such complex products. It has been found that the hybrid approach is the most efficient approach. The study proposes an approach to effectively manage risk in the product design process that hybridizes attributes of both the lean and agile design paradigms. The proposed approach has been validated using five case studies with 99% level of statistical confidence. The results of this study enable efficient development of complex products such as robotic systems towards realizing sustainable competitiveness.

Technological indicators and productive performance of dairy cattle farming in the city of Rondon do Pará, state of Pará, Brazilian Amazon

The objective of this study was to evaluate the technological level and productive performance of the milk producing units of the municipality of Rondon do Pará in the state of Pará. Data were collected through interviews with questionnaires, conducted at 55 dairy farms, which accounted for 43.3% of the milked cows in the municipality. The factors that characterize the systems of bovine milk production were estimated by means of factorial analysis using 12 variables representative of the production units surveyed. Five factors were extracted: F1 = size of the enterprise; F2 = environment and nutrition; F3 = technical assistance and herd management; F4 = animal health; F5 = schooling. From the scores associated with each factor, the index for productive performance of dairy cattle (DFPI) was calculated. The properties were classified into three levels of productive performance, including two considered to have a high level of DFPI, 16 with intermediate productive performance and 37 considered to have a low level of DFPI. There is a need to adopt technologies that promote the productive performance of dairy cattle in Rondon do Pará, as well as enable adaptation to socio-environmental public policies, with the aim of strengthening sustainable rural production through strategic actions that facilitate an increased technological level in farming systems production.

The Role of Personal Motivation in Sustainable Purchasing Practices

There is growing interest in identifying the drivers of and barriers to green purchasing, and many publications focus on motivational factors. However, the effects of these factors on the activities and means applied to sustainable purchasing are seldom investigated. This paper addresses this research gap and examines the impact of the motivational factors on green purchasing practices of the companies’. This paper also emphasises the role and motivational background of personal attitudes and reveals that there are differences among them. Based on the literature, a questionnaire was developed and a survey was completed in Hungary. The answers indicate that positive and compliant personal attitudes of purchasing managers’ have different drivers and barriers, while differences are also present in sustainable purchasing practices. Purchasing managers with a positive personal attitude have better green purchasing practices but mainly concerning product performance level activities, which do not require in-depth green management information.

Dairy cattle assessment using specialization indices and productive performance typicality

It would seem essential to create animals of the required types in view of the availability of various strains differing in the levels of productive performance within the breeds for dairy and dual-purpose production. Monitoring the herds of Black-and-White and Simmental cattle for the type of production (high production dairy type, dairy type, and duel-purpose: dairy-beef and beef-dairy types) was carried out using various methods. The extra milk yields from the high producing dairy cows of the Simmental breed and the Holstein F1 crossbreds as compared to the peers of the other types ranged from 469 kg to 1391 kg and from 555 kg to 1734 kg, respectively. Irrespective of any breed and selection, the cows of a dairy type as compared to the peers of a dual-purpose type tended to produce higher yields by 563 kg (P > 0.95), 1140 kg (P > 0.99), and 1173 kg (P > 0.99) from the cows of the Black-and-White breed, the Holstein breed of the domestic selection, and the Holstein breed of the American selection, respectively. The milk of dual-purpose cows as compared to the milk of dairy cows was characterized by higher butterfat content (by 0.06–0.08% on average). The methods applied to identify the parameters for conformation and production traits simultaneously are the most informative techniques to evaluate the production type of cows.

Pengembangan dan Implementasi Aplikasi Pengawasan Ternak Berbasis Android di Peternakan Bukit Aren Farm Majalengka

Bukit Aren Farm located in Majalengka, West Java is a company specialized in the broiler of the agriculture industry, farming broiler performed in different places and every breeding cattle carried monitored by the supervisory staff. Every day, staf record information manually about the animal in the cage that data will be used as a performance evaluation of animal production. The livestock management personnel encountered problems when running calculations of the evaluation product and efficiency livestock because the calculation process can be done if the existing data stored carefully and systematically, in particular the data recorded cattle in significant quantities, it would require much time for staff supervision to determine the level of production performance. Application developed using waterfall method. The waterfall model is composed of: requirements, design, implementation, verification, maintenance. To begin the design steps required observations or interviews to determine the needs of the system under design. Applications developed using CodeIgniter framework, angularjs and ionic based architecture. Results of the project is the application mobile livestock monitoring data storage that can serve the number of deaths, data on the number quarantine of chicken, and the amount of data that then feed use these data will generate a data value prices and feed consumption levels of livestock mortality information for the evaluation process in the livestock in line with the business processes of Bukit Aren Farm. The application has been tested by using black box method and the results of these tests indicate that all functions in the system has been well running on the Android operating system from version 4.1.

Ergonomic Redesign of a Traditional Jewelry-Polishing Workstation

Jewelry production is one of the largest employment sectors in the global economy. This case study focuses on the design of a jewelry-polishing workstation with the objectives of mitigating repetitive-motion injuries, improving worker productivity and efficiency, increasing polisher career longevity, and reducing the training time required for new polishers to reach the professional criterion level of production performance. The result is a new polishing workstation that meets the ergonomics and production requirements of jewelry polishers while improving their quality of life and extending the duration of their careers. The polishing station is based on the application of detailed ergonomic and user-centric methodologies.

When cost–effective design strategies are not enough: Evidence from an experimental study on the role of redundant goals

Projects have to meet interrelated time, cost and effectiveness goals. Surveys, such as CHAOS, consistently indicate that over 50% of the projects either significantly deviate from these goals or fail. Therefore, there is room for improvement in terms of project outcomes. This motivated us to explore improvement possibilities for the outcomes of design strategies that account for the interrelations between time, cost and effectiveness. We focus on a cost–effective (CE) design strategy that aspires to maximize the effectiveness-to-cost ratio (ECR) by deciding on: project schedules, resource allocations and a product performance level (i.e. effectiveness). We suggest a mathematical formulation to capture trade-offs between project scope decisions (such as project scheduling and resource allocations) and effectiveness. We conduct experiments, in which participants use a simulator to plan and execute a project according to the CE strategy with and without goals, based on solutions for the mathematical formulation. Contrary to some of the literature on goal-setting theory for complicated tasks, we found that appropriate goals improved the expected ECR while others did not have any impact. A better understanding of appropriate goal-setting in the context of project management may be important for improving projects outcomes.

Complexity, reliability and design: the coming monolithic revolution in manufacturing

A major component of IIASA's Technology–Economy–Society (TES) Program is a project to assess 'Computer Integrated Manufacturing' (CIM), by which is meant the whole range of application of computers to discrete parts manufacturing and assembly. The paper presents some interesting and new ideas about the nature of the forces driving the worldwide trend toward flexible automation. It suggests, in brief, that the demand for CIM arises from what Nathan Rosenberg has termed as 'mismatch', i.e. a problem that was created, in effect, by technological progress itself. In this case the 'problem' is that defects in manufacturing have become intolerable. The reason for that is that demand for higher and higher levels of product performance, over many decades, has required orders–of–magnitude increases in mechanical complexity, on the one hand, and higher precision, on the other. To satisfy these high standards requires a level of error control that increasingly precludes the use of human workers in direct contact with workpiecesas they move through the manufacturing system.

Effects of rumen-escape starch and coarseness of ingredients in pelleted concentrates on performance and rumen wall characteristics of rosé veal calves

The objective was to study the effect of rumen-escape starch and coarseness of ingredients in pelleted concentrates on performance, carcass quality and rumen wall characteristics in rosé veal calf production. Two alternative concentrates (Coarse and Slow) were compared with a traditional (Control) concentrate. Control was based on finely ground ingredients, whereas in Coarse, the same ingredients were coarsely ground resulting in a mean particle size before pelleting of 1.5 in Coarse and 0.6 mm in Control. Slow compared with Control and Coarse contained finely ground sorghum and corn instead of barley and wheat which increased the amount of rumen-escape starch to 59 compared with 22 g/kg in Control and Coarse. All concentrates had the same total starch (362 g/kg), NDF (168 g/kg), CP (154 g/kg) and DE (15.5 MJ/kg DM) content and a pellet diameter of 3.5 to 4 mm. Use of an ‘indicator of starch digestibility’ method gave a value of 98.6% for Control and Coarse and 91.1% for Slow (P < 0.001). A total of 57 Holstein bull calves (n = 19 per treatment) were offered one of the three concentrates ad libitum from weaning 2 1/2 months of age) to slaughter (<10 months of age). Concentrate intake was recorded individually. Barley straw was available ad libitum but intake was not recorded. Average daily gain (1.43 kg/day), concentrate conversion efficiency (3.7 kg DM concentrate/kg gain), LW at slaughter (386 kg), carcass weight (194 kg) and EUROP conformation (3.9) were not affected by type of concentrate (P > 0.05). Papillae length and shape evaluated in atrium ruminis and the cranial part of the ventral rumen sac at slaughter were not affected by type of concentrate (P > 0.05). Rumen wall characteristics showed degrees of plaque formation (i.e., papillary aggregation), hyperaemia and necrotic areas in all treatment groups, but with no general difference between type of concentrate (P > 0.05). Incidence of liver abscesses (LAs, 16%) was not affected by type of concentrate (P > 0.05). There were no differences in performance or rumen wall characteristics between liver-abscessed and non-abscessed calves. The results show a high level of production performance with the three types of pelleted concentrates and indicates that neither the more coarse ingredients nor the additional rumen-escape starch tested, when fed ad libitum, could improve rumen wall characteristics or reduce LAs of rosé veal calves.

Measuring the importance of product attributes and its implication in resource allocation

This paper reports on a critical review of the Importance-Performance Analysis (IPA) method using three different measures: customer self-stated importance, regression analysis and regression analysis with dummy variables. The study confirms that product attribute importance is an antecedent of attribute performance. The importance of product attributes from the customers’ point of view may change with the fluctuation in product performance level. The results of this research help in measuring the impact of service attribute performance on customer satisfaction, which in turn can help companies to identify the product attributes that have higher returns for the business.

Product price and performance level in one market or two separated markets under various cost structures and functions

Market characteristics, including intrinsic demand and customer sensitivity on price and product performance level, are distinct at different markets. Comparisons of various product development strategies in one market or two geographically separated markets are conducted for three classes of products: development intensive products (DIPs) with constant unit cost, marginal cost-intensive products (MIPs) with constant fixed cost, and marginal and development intensive products (MDIPs) with non-constant unit cost and fixed cost. Results show that larger demand size, less customer sensitivity on price and/or more sensitivity on performance level lead to more profit, a higher sale price and a not-lower product performance. The customer reservation or the saturation performance level should be generally adopted though the optimal performance level does exist occasionally. Unit cost and/or fixed cost must increase in performance at an increasing rate for the existence of one optimal performance level. Due to the impact of demand size, one high-end (low-end) MDIP or DIP could be introduced into one low-end (high-end) market at a different price if the demand size is significantly large in the low-end market. For DIPs, offering one niche high-end product is not worse than offering the low-end product into two markets. For MIPs with negligible fixed cost, the product line strategy is not worse than the standard product development strategy. Additionally, the product cost reduction approach adopted in one product line has significant effects on the best product development strategy and sequence.

Modelling trade-offs between livestock grazing and wader conservation in a grassland agroecosystem

The objective of this study was to model the trade-offs between ecological and productive performance of a grassland agroecosystem. We developed a dynamic model linking grass dynamics controlled by livestock grazing to stochastic population dynamics of two wader bird species with high conservation value. Bird dynamics were driven by both direct and indirect effects of grazing. Viable control framework was used to predict grazing strategies ensuring production and conservation and to generate the whole trade-off curve between ecological and productive performance. Bird population size was used as an indicator of ecological performance and the total number of grazing days defined productive performance. Model results show that conciliating ecological and productive performance implies a temporal shift in grazing sequences. The best ecological performance was obtained at intermediate levels of productive performance. Without grazing or with too low a grazing intensity, it was not possible to maintain any of the bird populations due to the indirect effects of grazing on habitat quality. However, too high a level of grazing implied fast population decline for both populations due to direct negative effects of grazing on nest survival. Field data on current grazing regimes and grass height showed a low proportion of suitable fields in our case study area. This result indicates an antagonism between direct and indirect effects of grazing on wader birds, implying the need of very specific management of grassland. Our results illustrate the fact that European grasslands are anthropic habitats which are highly dependent on human activity. In such habitats, trade-off curves are not expected to be strictly decreasing or increasing.

A critical analysis of European standards for thermal measurements at high temperatures: II. Recommendations for inclusion in a new standard

A critical examination of the current European and related standards for the guarded hot plate method has been carried out to address its suitability for measuring thermal performance properties of thermal insulations at elevated temperatures in the range 100 °C to 850 °C. An historical overview illustrating the significant potential problem areas is contained in part 1 of this paper. Part 2 presents a detailed discussion of the cause and effects of the various issues and associated parameters involved. These include:(a) Apparatus principles and design, including gap heat interchange and better control of radiation and edge loss effects. (b) Design parameters for the heater, including size, construction materials and heaters, adequate modelling, emittance of plates and temperature sensors. (c) Temperature measurement and control, and the effect of thermal degradation on its performance. (d) Specimen limitations. (e) Operation and performance checks, including the need for strict operation criteria and measurements on heating and cooling. (f) Needs for an adequate range of reference materials and/or transfer standards.Possible ways and means to eliminate or minimize these effects such that the necessary precision levels satisfy current European Union mandated levels of product performance are proposed. It is recommended further that as a result of these findings a new standard specifically for use of the method at high temperatures should be prepared. Also discussed are needs for additional research work believed necessary in certain areas in order to improve the precision further over the temperature range 100 °C to 850 °C.

Multivariate tolerance design for a quadratic design parameter model

The determination of tolerance allocations among design parameters is an integral phase of product/process design. Such allocations are often necessary to achieve desired levels of product performance. Parametric and nonparametric methods have recently been developed for allocating multivariate tolerances. Parametric methods assume full information about the probability distribution of design parameter processes, whereas, nonparametric methods assume that only partial information is available, which consists of only design parameter process variances. These methods currently assume that the relationship between the design parameters and each of the performance measures is linear. However, quadratic response functions are increasingly being used to provide better approximations of the relationships between performance measures and design parameters. This is especially prevalent where there is a multivariate set of performance measures that are functions of a common set of design parameters. In this research we propose both parametric and nonparametric multivariate tolerance allocation procedures which consider the more general case where these relationships can be represented by quadratic functions of the design parameters. We develop the corresponding methodology and nonlinear optimization models to accommodate and take advantage of the presence of interactions and other nonlinearities among suppliers.

Multivariate tolerance design for a quadratic design parameter model

The determination of tolerance allocations among design parameters is an integral phase of product/process design. Such allocations are often necessary to achieve desired levels of product performance. Parametric and nonparametric methods have recently been developed for allocating multivariate tolerances. Parametric methods assume full information about the probability distribution of design parameter processes, whereas, nonparametric methods assume that only partial information is available, which consists of only design parameter process variances. These methods currently assume that the relationship between the design parameters and each of the performance measures is linear. However, quadratic response functions are increasingly being used to provide better approximations of the relationships between performance measures and design parameters. This is especially prevalent where there is a multivariate set of performance measures that are functions of a common set of design parameters. In this research we propose both parametric and nonparametric multivariate tolerance allocation procedures which consider the more general case where these relationships can be represented by quadratic functions of the design parameters. We develop the corresponding methodology and nonlinear optimization models to accommodate and take advantage of the presence of interactions and other nonlinearities among suppliers.

Multivariate tolerance design using quality loss

The determination of tolerance allocations among design parameters is an integral phase of product/process design. Such allocations are often necessary to achieve desired levels of product performance. We extend our prior research on tolerance allocation by developing both parametric and nonparametric methods for a multivariate set of performance measures that are functions of a common set of design parameters. The parametric method is novel and assumes full information about the probability distribution of design parameter processes. The proposed nonparametric method assumes that only partial information is available and significantly extends prior research by considering a more contemporary and realistic model for manufacturer costs. For both methods we derive economically based models that represent the costs, both internal (supplier) and external (manufacturer), of tolerance allocation under several different process scenarios. These scenarios are based on the manner of disposition of nonconforming product. For the parametric methods we derive tolerance allocation solutions that jointly minimize expected total cost of the supplier and manufacturer. For the nonparametric methods we derive solutions for tolerance allocation that jointly minimizes the maximum expected total cost. An example in the fabrication of a rubber tread compound is used to: (i) demonstrate the implementation of our proposed methodologies for tolerance allocation; (ii) illustrate and compare the nonparametric and parametric methods; land iii) assess the sensitivity of optimal tolerance allocations to changes in process model types, cost coefficient estimates, and manner of disposition of nonconforming product.

Multivariate tolerance design using quality loss

The determination of tolerance allocations among design parameters is an integral phase of product/process design. Such allocations are often necessary to achieve desired levels of product performance. We extend our prior research on tolerance allocation by developing both parametric and nonparametric methods for a multivariate set of performance measures that are functions of a common set of design parameters. The parametric method is novel and assumes full information about the probability distribution of design parameter processes. The proposed nonparametric method assumes that only partial information is available and significantly extends prior research by considering a more contemporary and realistic model for manufacturer costs. For both methods we derive economically based models that represent the costs, both internal (supplier) and external (manufacturer), of tolerance allocation under several different process scenarios. These scenarios are based on the manner of disposition of nonconforming product. For the parametric methods we derive tolerance allocation solutions that jointly minimize expected total cost of the supplier and manufacturer. For the nonparametric methods we derive solutions for tolerance allocation that jointly minimizes the maximum expected total cost. An example in the fabrication of a rubber tread compound is used to: (i) demonstrate the implementation of our proposed methodologies for tolerance allocation; (ii) illustrate and compare the nonparametric and parametric methods; and (iii) assess the sensitivity of optimal tolerance allocations to changes in process model types, cost coefficient estimates, and manner of disposition of nonconforming product.

Multicriteria Optimization in Product Platform Design

A product platform is a set of common components, modules or parts from which a stream of derivative products can be created. Product platform design requires selection of the shared parts and assessment of the potential sacrifices in individual product performance that result from parts sharing. A multicriteria optimization problem can be formulated to study such decisions in a quantitative manner at the product performance level. Studying the Pareto sets that correspond to various derivative products leads to a systematic methodology for design decision making. Design of a nail gun platform is used to illustrate the concepts presented.