S.H. Tang

A hybrid genetic-heuristic algorithm for scheduling of automated guided vehicles and quay cranes in automated container terminals

Containers have been used in past decades increasingly as one of the most important transportation tools. Containers have revolutionized cargo shipping and thus changed the world trade systematically. Container terminals as the transhipment facility play a valuable role in performance of this transportation system. Improvement of this facility has been widely considered in literatures. Automated container terminals (ACTs) have been introduced to pursue this purpose. In ACTs various transport vehicles are automated and integrated to each other. Automated guided vehicles (AGVs) are used in ACTs to handle containers between quay cranes and storage yards. Usually scheduling of the AGVs is known as the key factor to improve the performance of ACTs. This paper proposed a heuristic algorithm to schedule the AGVs concurrently with quay cranes. A genetic algorithm is proposed to optimize the simultaneous scheduling of AGVs and QCs. The results showed that proposed genetic algorithm can be used in practical implications while its running time is reasonably low.

Lot Streaming and Preventive Maintenance in a Multiple Product Permutation Flow Shop with Intermingling

A mathematical model forlot streaming problem with preventive maintenance was proposed. A mixed-integer linear model for multiple-product lot streaming problems was also developed. Mixed-integer programming formulation was presented which will enable the user to identify optimal sublot sizes and sequences simultaneously. Two situations were considered:1) all machines were available, and 2) all machines needed preventive maintenance tasks. For both situations a new mixed-integer formulation was developed. To demonstrate the practicality of the proposed model, numerical example was used. It showed that the percentage of make span reduction due to lot streaming in permutation flow shop is 54% when compared to consistent sublots with intermingling case.

Construction of fuzzy ¯X-S control charts with an unbiased estimation of standard deviation for a triangular fuzzy random variable

Statistical process control and Shewhart control charts are used by organizations to aid in process understanding, assessing process stability, and identifying changes to improve the quality of the product. Shewhart control charts only considered uncertainty caused by randomness while in practice, uncertainty caused by vagueness, ambiguity, and/or incomplete information are also observed. In this article, fuzzy ¯ X − S control charts which handle both kinds of uncertainty simultaneously are developed using fuzzy random variables. For this purpose, the unbiased estimation of standard deviation for a triangular fuzzy random variable is introduced and utilized to construct the fuzzy ¯ X − S control charts. Then, a detailed average run length study is performed to evaluate the decisions regarding sample size and accepted out-of-control level (). A comparison study is performed to verify the proposed technique by comparing its performance based on average run length with previous technique in the literature. The result shows that the proposed technique could improve the detection of abnormal shift in process mean 0.1% to 30% depending on sample size and shift. Finally, the proposed fuzzy control charts are validated through a case study of noodle production in food industry.

Managing Uncertainty in Supply Chain Management of Vessel Chartering in Oil & Gas Industry

Uncertainty is a condition that needs to be dealt with by Supply Chain Management (SCM) in many organization. The factors that contributed to the uncertainty have to be understood in order to manage it in the best and practical ways. Uncertainty in an Oil & Gas firm propagates through the supply chain network including vessel sourcing activities that involved offshore transportation and installation activities. It is important to have a sustainable and reliable vessel supply in supporting offshore activities. Therefore, this paper presents the analysis of uncertainty in supply chain management process of vessels in the Oil & Gas Industry. This research is conducted by analysing quantitative data from vessel sourcing database focuses on uncertainty recorded from January to August 2012. It has been found that, the major causes of uncertainty is due to the unavailability of vessel with 51% of causes of uncertainty recorded. This is due to the increment of vessel utilization from year 2011 to 2012. However the uncertainty can be appropriately managed by implementing product departmentalization instead of customer departmentalization which is currently practiced by the firm under study. It can be concluded that, there are four factors that contributed to uncertainty which are vessels availability, project management plan, project requirement, and vendor reliability.

Illustration and Model Verification for an Inter-Cell and Intra-Cell Facility Layout Problem in a Cellular Manufacturing System

In a Cellular Manufacturing System (CMS), parts based on their similarities are grouped into part families, and are assigned to one or more machine cells to be manufactured. In the design of a CMS, facility layout problem aims to arrange machine cells in the shop floor and facilities in the machine cells in order to have an efficient layout. In this study, a previously developed cellular layout model will be illustrated and validated for a well-known case from the literature. Lingo optimization software version 12.0 and an enumeration method will be used to solve, and validate the model. The results of this study show the validity of the proposed model.

Fuzzy mean and range control charts for monitoring fuzzy quality characteristics: A case study in food industries using chicken nugget

Organizations must improve or at least maintain the quality of their products to be competitive in todays market. Thus, developing a new approach which could utilize more information from the production process has become an inevitable quality improvement program for each organization. In current study, a fuzzy mean and range control charts were developed to monitor the production process. Fuzzy control charts could handle the uncertainty due to vagueness, ambiguity and/or incomplete information in addition to the inherent uncertainty due to randomness in quality characteristic measurements. The proposed fuzzy control charts were validated through a case study at the chicken nugget production company by collecting data from the factory floor and comparing it to the traditional Shewhart control charts which have been already applied by the factory for monitoring the process. The results reveal that the proposed fuzzy control charts could detect abnormal shifts in the production process more accurately than the traditional Shewhart control charts, as they had used more information from the process. The proposed approach has several benefits for the company by improving the quality and increasing the productivity.

Minimization of Residual Stresses in Submerged Arc Welding Process of Oil and Gas Steel Pipes by Committee Machine

Submerged arc welding (SAW) is a well-known method to weld seam in manufacturing of large diameters steel pipes in oil and gas industry. The main subject of SAW design is selection of the optimum combination of input variables for achieving the desired output variables of weld. Input variables include voltage, amperage and speed of welding and output variables include residual stresses due to welding. On the other hand, main target in multi response optimization (MRO) problem is to find input variables values to achieve to desired output variables. Current study is a combination and modification of some works of authors in MRO and SAW subjects. This study utilizes an experiment design according to Taguchi arrays. Also a committee machine (CM) modeling the problem by CM using two approaches. The first CM consists eight experts with traditional approach in computation and second CM includes elite experts. Genetic algorithm was applied to find CM weights and desired responses. Results show that proposed approach in CM has a smaller root mean squire error (RMSE) than traditional approach. The validation of CM model is done by comparison of results with simulation of SAW process and residual stresses in a finite element environment. Finally, the results show few differences between the real case responses and the proposed algorithm responses.

Integrated Dispatching Model of Automated Lifting Vehicles, Quay Cranes and Yard Cranes at Automated Container Terminal

Integration of various types of handling equipment is one of the important methods to improve the efficiency of processes and productivity of a container terminal. Using ALVs, because of their ability in lifting a container from the ground by themselves, can reduce the delay of loading and unloading tasks in automatic container terminals.In this paper, a mixed-integer programming model, which considers the integration of ALVs, Quay Cranes and Yard Cranes, is developed. This model minimizes the makespan of the loading and unloading activities in an Automatic Container Terminal with limited buffer spaces.

The Impact of Information Technology Investment on Supply Chain Capabilities: A Review

In the manufacturing industry, control of information and movement of material from suppliers at all levels is a critical matter.IT helps to manage all information among suppliers. Pervious research have shown that IT has indirect effects on business performance. Moreover, there are many discussions about the capabilities and mediate the relationship between IT and business performance such as supply chain performance and supply chain process integration. The integration of dissimilar supplementary resources can produce interaction that can cause better performance.

A Combinational Approach for Experts of Committee Machine in Wire Bonding Problem Solving

There are three phases to solve multiple response optimization (MRO) problems. They are experiment design, modelling and optimization. Different committee machines (CMs) are applied for modeling of MRO problem. Two kinds of CM introduced by current authors in recent works. Initial approach includs utilization of all experts in CM and finally sequentilal combinational model (SCM) is created. Current study proposes a combinational approach to filter and select the best experts to create CM which yields optimum combinational model (OCM). Also , there was another modeling with name point approach model (PAM). This study investigated two different features of different SCMs, PAM and OCM in a famous MRO problem with name wire-bonding. This problem was defined in 1997 and then, several researchers solved it in next years. The results show PAM has minimum RMSE but its global desirability is low. Also overall RMSE has a slightly fall from SCMs to OCM , whereas, there is gently rise in global desirability from SCMs to OCM and consequently proposed approach or OCM provides superior results.