Iot based laundry services: an application of big data analytics,intelligent logistics management,and machine learning techniques

The authors propose an innovative Internet of Things (IoT) based E-commerce business model Cloud Laundry for mass scale laundry services. The model utilises big data analytics, intelligent logistics management, and machine learning techniques. Using GPS and real-time update of big data, it calculates the best transportation path and update and re-route the logistic terminals quickly and simultaneously. Cloud laundry intelligently and dynamically provides the best laundry solutions based on the current state spaces of the laundry terminals through the user's specifications and thus offers local hotel customers with convenient, efficient, and transparent laundry services. Taking advantage of the rapid development of the big data industry, user interest modelling, and information security and privacy considerations, cloud laundry uses smartphone terminal control and big data models to maintain customers’ security needs. Different from the traditional laundry industry, cloud laundry companies have higher capital turnover, more liquidity, and stronger profitability. Therefore, this new generation of smart laundry business model could be of interest to not only academic researchers, but E-commerce entrepreneurs as well.     

Optimisation of the aggregation and execution rates for intersecting operation sets: an example of machining process design

A sequence of multiple parts is processed on a multi-position transfer line of conveyor type. This sequence consists of identical subsequences (batches). The sets of operations executed for each part at each position are given and these sets for different parts can intersect. Some operations executed at one position can be aggregated into blocks of operations. Each block is executed at a uniform rate (in particular, feed per minute) by a common drive unit. The set of potentially feasible blocks is specified. We consider the situation when the sets of operations for different blocks do not intersect and each potential block can be executed either completely aggregated (i.e. as one block) or completely disaggregated (individually). Aggregation reduces the investment costs, but can increase the consumption of tools due to excluding the individual selection of rates for aggregated operations. The accepted option of the aggregation and the rates of operations remain invariable during the line functioning. The problem is to select the optimal option of aggregation and rates of all operations that minimise the total batch processing cost while ensuring the required line productivity. A mathematical model of the problem and a two-level decomposition method for its solution are proposed. The statement of the problem and the results of its solution are illustrated on a real industrial example. The developed model and method can be applied to solve similar problems arising in other domains.     

Simulation in the design and operation of manufacturing systems: state of the art and new trends

As the industrial requirements change at a rapid pace due to the drastic evolution of technology, the necessity of quickly investigating potential system alternatives towards a more efficient manufacturing system design arises more intensely than ever. Manufacturing systems simulation has proven to be a powerful tool for designing and evaluating a manufacturing system due to its low cost, quick analysis, low risk and meaningful insight that it may provide, improving thus the understanding of the influence of each component. Simulation comprises an indispensable set of IT tools and methods for the successful implementation of digital manufacturing. It allows experimentation and validation of product, process, and system design and configuration. This paper investigates the major historical milestones in the evolution of manufacturing systems simulation technologies and examines recent industrial and research approaches in key fields of manufacturing. It describes how the urge towards digitalisation of manufacturing in the context of the 4th Industrial revolution has shaped simulation in the design and operation of manufacturing systems and reviews the new approaches that have arisen in the literature. Particular focus is given to technologies in the digitalised factories of the future that are gaining ground in industrial applications simulation, offering multiple advantages.     

Tempex: An expert system for temperature control in an injection moulding process

Current developments in expert system technology make it possible to devise systems for on-line quality control. Knowledge can be acquired and coded into a program to enable the operator or foreman to take immediate action to maintain product quality level through on-line monitoring. This paper presents TEMPEX, a knowledge-based statistical process control system for controlling the temperature in an injection moulding machine. The system is able to determine the process limits, detect out of control situations, find possible assignable causes and suggest corrective actions. The system is based on Leonardo, an expert system shell with a hybrid knowledge representation facility enabling the use of rules, rulesets, frames and procedures. The system contains 207 rules, 19 rule-sets, 315 frames and 28 procedures.     

新疆某办公楼蒸发冷却空调系统应用及效益分析

本文旨为干燥地区办公建筑蒸发冷却空调系统的设计、设备选型、调试、运行的全过程提供基础理论支持,从系统设计、设备选型入手,对系统调试,应用情况及经济,节能效益进行分析。还提出了解决系统水流量异常的合理方案,且测得夏季室内温湿度符合设计要求时,温度应在24℃~27℃,湿度应在45%~70%,方可满足室内舒适性要求,维持良好的室内空气品质。本系统相较于传统空调系统,其初期投资高出10万元,但运行费用可节省32.20%,增量分析回收时间为2.04年;耗水量可节省60.29%,耗电量可节省27.4%,可节约标准煤35.84吨。     

Successful implementations of MES in Korean manufacturing SMEs: an empirical study

This study explores the factors that affect the successful implementation of the Manufacturing Execution Systems (MES) in small and medium manufacturing enterprises (SMMEs). To this end, a survey was carried out. Responses from 163 SMMEs were analysed. The results found that all hypothesised variables including top management support, sufficiency of investment, capacity of the system developer, and user participation were critical factors for successful MES implementation in SMMEs. This study is the first empirical study on the successful implementation of MES in SMMEs in the Asia/Pacific region.     

Quality versus productivity in service production systems: an organisational analysis

The study presents an organisational analysis into the linked issues of service productivity and perceived service quality. The operations management literature postulates that a trade-off exists between service productivity and perceived service quality, an assertion which is supported by evidence from managerial experiences and other academic researches. However, is it possible to prevail over the trade-off between productivity and perceived quality? Further, what is the effect of the trade-off on company profitability? To respond to these questions, a retrospective longitudinal study is performed, based on analysis of data collected from 52 offices of a major European banking group over the years 2010–2011. A first analysis verifies the existence of the trade-off. A second then examines the suitability of the employee incentive system intended to overcome the trade-off. Finally, a multiple linear regression model is developed in order to verify whether service productivity and perceived service quality impact on company profitability, and to what extent.     

Towards data-driven approaches in manufacturing: an architecture to collect sequences of operations

The technological advancements of recent years have increased the complexity of manufacturing systems, and the ongoing transformation to Industry 4.0 will further aggravate the situation. This is leading to a point where existing systems on the factory floor get outdated, increasing the gap between existing technologies and state-of-the-art systems, making them incompatible. This paper presents an event-based data pipeline architecture, that can be applied to legacy systems as well as new state-of-the-art systems, to collect data from the factory floor. In the presented architecture, actions executed by the resources are converted to event streams, which are then transformed into an abstraction called operations. These operations correspond to the tasks performed in the manufacturing station. A sequence of these operations recount the task performed by the station. We demonstrate the usability of the collected data by using conformance analysis to detect when the manufacturing system has deviated from its defined model. The described architecture is developed in Sequence Planner – a tool for modelling and analysing production systems – and is currently implemented at an automotive company as a pilot project.     

Restabilization in structures susceptible to localized buckling: an approximate method for the extended post-buckling regime

Localized buckling in structures has been extensively studied in the context of simple nonlinear models which capture the essence of the phenomenon near the lowest critical load. In this study we apply a non-periodic Rayleigh–Ritz procedure to track localizations into the far post-buckling regime where the structure regains stability after the initial destabilization. The results are compared against independent numerical solutions and good agreement is found.     

Treatment and recycling system optimisation with activity-based costing in WEEE reverse logistics management: an environmental supply chain perspective

Waste electrical and electronic equipment (WEEE) reverse logistics management has increasingly received much attention in recent years not only because of the fast increase of WEEE but also the legislations in many developed countries. This paper focuses on the treatment and recycling system, and proposes a two-stage multi-objective decision framework. In the treatment stage, the responsible producer selects treatment suppliers under extended producer responsibility by a pre-emptive goal programming model. After the wastes are depolluted and transformed to recyclable materials, the process enters the recycling stage in which the decision-maker plans the reclaimed material production by a linear programming model for profit maximisation. An illustrative case study is presented, and the sensitivity analyses show that the ranking of suppliers is more stable than the quantities allocated to suppliers under different priority structures, so ranking of suppliers should also be given attention in such multi-objective decision-making. In addition, a decision model with environmental constraints can reduce the production of the products that have more environmental impacts.