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The Economic and Environmental Impact of Paper Recycling
Published in Roger A. Sedjo, R. Neil Sampson, Joe Wisniewski, in Forestry, 2020
Using a production value of waste paper based on the prices of fossil fuels and round timber at the beginning of 1995, the most economical utilization rate for the Scandinavian forest industry is 57 per cent and 84 per cent for the forest industry in the rest of Western Europe. Thus, the economic optimization shows that from the perspective of business economics, a high utilization rate is profitable. If hydroelectric power is used in pulp and paper production and the Scandinavian forest industry is forced to decrease the utilization rate by 10 per cent, the marginal loss is about 5.5 USD/ton. On the other hand, if the electricity used is produced from fossil fuels, the loss is about 6.5 USD/ton. While mandatory utilization rates are set, the Model is free to optimally determine the admixture of waste paper for different products.
The Use of Reusable Plastic Containers in Tomato Logistics System
Published in Ifeyinwa Juliet Orji, Frank Ojadi, The Circular Supply Chain, 2023
Ifeyinwa Juliet Orji, Frank Ojadi
Cycle time is a crucial factor in the management of CLSCs. Achieving a short cycle time and thus a high utilization rate per unit promotes the economic efficiency of the system. From the point of view of the RPC service provider, it would be preferable to exercise control over as much of the supply chain as possible. This will not only shorten cycle time but also improve visibility. For this reason, the backhaul operation should be handled by the service provider.
Metrics
Published in Gerhard Plenert, Joshua Plenert, Strategic Excellence in the Architecture, Engineering, and Construction Industries, 2018
Gerhard Plenert, Joshua Plenert
The utilization rate is the percentage of time spent working on billable projects in comparison to the total hours worked. It’s common for the production staff to have a utilization rate of 70%–85% while a manager may have a utilization rate of around 60%–70%. The utilization rate is calculated as follows:
Configuring lean manufacturing and supply chain risk management: a cluster analysis
Published in Production Planning & Control, 2023
Kihyun Caleb Park, Mark M. Yang, James J. Roh
Leaners are the companies that are highly oriented towards implementing lean- or efficiency-driven practices focussing on low cost, minimum inventory and waste, and shorter lead time, rather than implementing practices that concentrate on risk-hedging or enhancing responsiveness. These types of companies often implement lean manufacturing to better achieve cost-effectiveness in their manufacturing operations. However, the operational cost efficiency is not the only reason. Other key drivers include production scheduling, resource utilization, inventory management, cycle time reduction, and so on. Firms can achieve effective production scheduling by standardizing production work and adopting JIT and Kanban practices to maximize resource utilization (Shah and Ward 2007). Lean practices are not limited but include 5S, value stream mapping, waste analysis, total quality management, and total production maintenance. Their primary concern lies in eliminating waste while continuously improving quality (Vonderembse et al. 2006). By implementing lean manufacturing in their plants and warehouses, firms can reduce cost, increase turnover, and most important, systematically improve efficient processes, guaranteeing a greater utilization rate and resulting in improved operations. It is also noteworthy that lean operations can be applied to managing firms’ external suppliers. The way firms handle and manage their own inventories can be directly applied to their suppliers when integrating them into their larger supply chain systems (Yadav, Seth, and Desai 2018).
Determining the environmental impact of material hauling with wheel loaders during earthmoving operations
Published in Journal of the Air & Waste Management Association, 2019
Hassanean S.H. Jassim, Weizhuo Lu, Thomas Olofsson
As discussed above, Figures 9 and 11 show that according to the sensitivity analysis, the fuel consumption per cubic meter can be reduced in practice by increasing wheel loaders’ utilization rates during earthmoving activities and using their full bucket capacity (i.e. maximizing their payload). The utilization rate can be regarded as a measure of the overall operational efficiency of a construction machine fleet configuration; it is sensitive to the types, capacities, and numbers of machines that are selected to work alongside the wheel loaders, and the degree to which their hauling capacities complement those of the wheel loaders. Utilization can also be regarded as the opposite of idling; consequently, the first step towards improving the utilization rate is to minimize the idle time of equipment. Increasing the utilization rate of wheel loaders would significantly reduce their fuel consumption per cubic meter hauled if all other factors affecting operating efficiency remain constant. The third most important input parameter was the bucket payload. Optimizing the bucket payload also reduces fuel consumption per cubic meter hauled (if other productivity-affecting parameters such as cycle times are held constant) because it ensures that the maximum bucket capacity is not exceeded and the engine is not overloaded.
Decision-making in smart manufacturing: A framework for performance measurement
Published in International Journal of Computer Integrated Manufacturing, 2023
Shreyanshu Parhi, Kanchan Joshi, Milind Akarte
The SMPIs used to quantify the soft measures are mentioned and deliberated here. The indicator for soft measures evaluates the outcomes of the SMPMs. It is because the soft SMPMs are difficult to measure directly. For Instance, using smart scheduling approaches can enhance the utilization rate of resources in the manufacturing system. Therefore, the potential SMPIs for the valuation of smart scheduling measures is Resource Utilization (Abedini et al. 2020). The indicators to assess different soft measures are discussed next. Portability: Portability ensures the ability of the smart manufacturing system to transfer information from one asset in the network to another. is responsible for gauging the network infrastructure and ensuring greater traceability and transparency of the smart manufacturing systems (Muhuri, Shukla, and Abraham 2019; Guo et al. 2021). The is assessed through the scale to determine the degree of structuredness of data in the system (Bizer, Heath, and Berners-Lee 2011). Each point in the scale describes certain properties of the system, which need to be taken into consideration to evaluate for a system. The formulation of adopted from Spagnuelo, Bartolini, and Lenzini (2020) is indicated next.Vectors of Intelligence: The evaluation of intelligence for a manufacturing system is a difficult task due to the complex technologies involved in constructing its architectures (Morgan et al. 2021; Jones, Romero, and Wuest 2018; Lee, Jin, and Bagheri 2017). Additionally, intelligence is multidimensional in nature and is assessed through vectors of intelligence, i.e. (Zhang and Tao 2016). The used are the Cost function for problem-solving ; Response time to react to any situations on the shop floor ; and Problem-Solving Capability i.e. (Zhong et al. 2017; Tao et al. 2014; Far and Cobzaru 2002).