Shulin Lan

Big Data for supply chain management in the service and manufacturing sectors

A state-of-the-art research on Big Data in SCM is reviewed.A discussion from analyzing current movements on the Big Data for SCM in service and manufacturing world-wide is presented.Current challenges, opportunities, and future perspectives Big Data are highlighted. Data from service and manufacturing sectors is increasing sharply and lifts up a growing enthusiasm for the notion of Big Data. This paper investigates representative Big Data applications from typical services like finance & economics, healthcare, Supply Chain Management (SCM), and manufacturing sector. Current technologies from key aspects of storage technology, data processing technology, data visualization technique, Big Data analytics, as well as models and algorithms are reviewed. This paper then provides a discussion from analyzing current movements on the Big Data for SCM in service and manufacturing world-wide including North America, Europe, and Asia Pacific region. Current challenges, opportunities, and future perspectives such as data collection methods, data transmission, data storage, processing technologies for Big Data, Big Data-enabled decision-making models, as well as Big Data interpretation and application are highlighted. Observations and insights from this paper could be referred by academia and practitioners when implementing Big Data analytics in the service and manufacturing sectors.

A two-level advanced production planning and scheduling model for RFID-enabled ubiquitous manufacturing

An RFID-event driven mechanism is used to integrate planning and scheduling.RFID production shopfloor data was used to obtain APPS parameters.Release strategy is efficient to reduce the total tardiness by 44.46% averagely. Radio frequency identification (RFID) technology has been used in manufacturing industries to create a RFID-enabled ubiquitous environment, in where ultimate real-time advanced production planning and scheduling (APPS) will be achieved with the goal of collective intelligence. A particular focus has been placed upon using the vast amount of RFID production shop floor data to obtain more precise and reasonable estimates of APPS parameters such as the arrival of customer orders and standard operation times (SOTs). The resulting APPS model is based on hierarchical production decision-making principle to formulate planning and scheduling levels. A RFID-event driven mechanism is adopted to integrate these two levels for collective intelligence. A heuristic approach using a set of rules is utilized to solve the problem. The model is tested through four dimensions, including the impact of rule sequences on decisions, evaluation of released strategy to control the amount of production order from planning to scheduling, comparison with another model and practical operations, as well as model robustness. Two key findings are observed. First, release strategy based on the RFID-enabled real-time information is efficient and effective to reduce the total tardiness by 44.46% averagely. Second, it is observed that the model has the immune ability on disturbances like defects. However, as the increasing of the problem size, the model robustness against emergency orders becomes weak; while, the resistance to machine breakdown is strong oppositely. Findings and observations are summarized into a number of managerial implications for guiding associated end-users for purchasing collective intelligence in practice.

Towards product customization and personalization in IoT-enabled cloud manufacturing

Customized/personalized products are gaining more shares in today’s product market. Such products need collective efforts from consumers, manufacturers and third parties. This requirement has not been well addressed due to both market and technology factors. On the other hand, the Internet of Things (IoT) provides real-time sensing/actuating ability and fast transmission capability of data/information, so that remote operation of manufacturing activities and efficient collaboration among stakeholders are greatly facilitated. This provides great opportunities to address the requirement mentioned above. Thus we propose a full-connection model of product design and manufacturing in the IoT-enabled cloud manufacturing environment. The proposed model uses social networks to connect multiple parties and facilitate open innovations, and use IoT to glue physical space to cyber space and cloud manufacturing to provide various elastic services, so that the on-demand workspace, interaction, information sharing or collective problem solving are enabled. We also propose a supporting infrastructure for this model using the latest information and communication technologies. Finally, we present a case study of an RFID enabled production system for customized and personalized product with the ability to enable a new paradigm of “dynamic processes and close collaborations among different roles” and ensure robust production.

A customer satisfaction evaluation model for logistics services using fuzzy analytic hierarchy process

– As the modern manufacturing twining seamlessly with logistics operations for value adding services, logistics service is becoming more and more significant. Under this research background, the purpose of this paper is to introduce an innovative evaluation model for customer satisfaction using fuzzy analytic hierarchy process (FAHP). , – This model uses triangular fuzzy concept to determine the weight of each index so that subjective or objective weighting is addressed. A case study from two large express companies in China is used to demonstrate the feasibility and practicality of the proposed model for examining customer satisfaction. , – One of the key findings is that Company B has higher customer satisfaction than Company A due to its quick response and flexible logistics strategy. This paper has several contributions. First, A FAHP-based customer satisfaction evaluation model is proposed for the logistics service. Second, the triangular fuzzy concept is introduced to determine the weight of each index so as to addresses the limitation of subjective or objective weighting method. Third, a case study demonstrates the implementation of the model. , – First, this paper considers the fuzzy AHP for the customer satisfaction evaluation. Comparing with other multi-criteria decision-making methods like data envelopment analysis, evidential reasoning approach, and multi-attribute value theory will be carried out in the near future. Second, the manufacturing modes like make-to-order, make-to-stock, and mass-customized production may have different logistics support so that the final products may reach the final targets quickly. How to evaluate various mode-based logistics and their customer satisfactions have great significance. Finally, Big Data-enabled customer satisfaction evaluation approaches may be a possible solution. , – Based on the data from questionnaire, it is found that, in practical applications, manufacturing enterprises should amend the index system according to the specific business scope and the production characteristics. Manufacturing enterprises need to collect large amounts of data through market research and conduct the measurement on the related coefficient between the measurement indicators and customer satisfaction degree. After that, they can make sorting and filtering on the measurement index according to the measurement results. , – Customer satisfaction is very important to manufacturing and logistics enterprises due to its time constraints. The physical products with services like logistics are paid close attention to by the final customers. , – The contribution of this paper is as follows: a FAHP-based customer satisfaction evaluation model is proposed for the logistics service; triangular fuzzy concept is introduced to determine the weight of each index so as to addresses the limitation of subjective or objective weighting method; a case study was used to demonstrate the implementation of the model. One of the key findings is that Company B has higher customer satisfaction than Company B due to its quick response and flexible logistics strategy.

Data analysis for metropolitan economic and logistics development

Quantitative examination of relations between metropolitan logistics and economy.Objective weight determination for indicators in the evaluation index systems.Regression analysis of the development of metropolitan logistics and economy.Correlation and regression analysis between economic forms and logistics subsystems. Logistics industry is an integral sector encompassing transportation, warehousing, handling, circulation and processing, delivery and information technology. With the progress of economic globalization and integration, logistics industry has become a new momentum driving the fast development of national and regional economy. The close relationship between economic development and logistics advancement receives wide attention from the academia. However, current research on the coordination between economy and logistics mostly focuses on concept interpretation, and qualitative discussions. Very rarely do scholars conduct quantitative analysis on the coordination of metropolitan economy and logistics. To fill this gap, we first examine whether there exist interactions between metropolitan logistics and economy by building evaluation index systems for metropolitan logistics and economy. Then we introduce the entropy method and Granger causality test to evaluate and test the level of logistics and economic development in five cities: Beijing, Shanghai, Guangzhou, Chongqing, and Tianjin from 2009 to 2013. From the dimensions of regional economic investment, regional economic capacity and strength, we finally test the relationship between three economic subsystems and three logistics subsystems to further validate the relationship between metropolitan economy and logistics.

Cloud service-oriented dashboard for work cell management in RFID-enabled ubiquitous manufacturing

This article aims at developing a service-oriented dashboard for operators and supervisors of manufacturing shopfloor work-cells to realize information visibility and traceability effectively with cloud and RFID (radio frequency identification) technologies. The work is based on a case of an illustrative assembly line consisting of a number of work cells. The dashboard is deployed for facilitating assembly operations in ubiquitous manufacturing environment. The utilization of the system leads to significant improvements in work cell productivity and quality, operational flexibility and decision efficiency.

A real-time RFID-driven model for two-level production decision-making

This paper is motivated by a real-life production company that has been using RFID technology for supporting its production decision-making, which is divided into production planning and scheduling. Using the concept of advanced production planning and scheduling within hybrid flowshop environment, a real-time RFID-driven model is proposed to twining production planning and scheduling so that these two levels could be synchronized. In experimental examinations, this paper compares this model with rule-based solutions. It is observed that this proposed model is able to reduce the total tardiness comparing with priority-based rules, material-based rules, and SPT.

Inventory hedging and coordination under inventory-level-dependent demand

This paper considers an inventory coordination problem in a group company where the group headquarter manages a centralized distribution center (HQ-CDC) providing inventory spaces and services for its subsidiary companies whose demands are inventory-level-dependent. To deal with uncertainty in inventory management, subsidiaries usually reserve more inventory spaces than their actual demands. This extra inventory space strategy is called “inventory hedging” in this research. As a result, subsidiaries may reserve excessive spaces which are never required for their business operations, leading to inconsistency with the lean warehousing and logistics strategy that the HQ-CDC would like to implement. This paper theoretically examine if the inventory hedging strategy is advantageous to subsidiaries, and if so how best such a strategy should be implemented. A coordination scheme with dynamic pricing is introduced here to coordinate the implementation of the inventory hedging strategy. Two types of prices are introduced. One is the basic price used for block-reserving inventory spaces. The other price is the “hedging price” which is the extra amount to the basic price in addition charged for the space more than the actual demand. Two models are developed. In one model, a Nash game is played to reach an optimal strategy for both parties. In the other model, a Stackelberg game is played in which the HQ-CDC serves as the leader. It is demonstrated that the coordination scheme through dynamic price can successfully reduce inventory hedging amount required by the subsidiaries and can increase the HQ-CDCs profit, as compared to the decentralized decision model without considering the hedging price.

Open and collaborative product design and production in IoT-enabled manufacturing cloud

Customized/personalized products are gaining more shares in todays product market. Such products need collective efforts from consumers, manufacturers and third parties. On the other side, the Internet of Things (IoT) with pervasive sensing/actuating/networking ability greatly facilitates remote operation of manufacturing activities and efficient collaboration among stakeholders. This provides great opportunities to the above demand. Thus we propose a full-connection model of product lifecycle in the IoT-enabled cloud manufacturing environment. The model uses social networks to connect multiple parties and facilitate open innovations, IoT to glue physical space to cyber space and cloud manufacturing to provide various elastic services, so that the on-demand workspace, interaction, information sharing or collective problem solving are enabled. We also propose a supporting infrastructure for this model using the latest information and communication technologies. Finally, we present a RFID (Radio-frequency identification) enabled production system for customized/personalized products with the ability to enable a new paradigm of “dynamic processes and close collaborations among different roles” and secure robust production.