Description:
This study focuses on cost and schedule issues of international development (ID) projects. Through empirical analysis we examine ID project cost and schedule performance and the main reasons for poor project outcome. We look at 100 projects that are sponsored by the Asian Development Bank and hosted by several Asian countries. The study identifies that most late projects experience cost underrun – an unusual cost and schedule variation relation in projects. Further we identify the root causes of project delay and cost underrun. Research findings will benefit ID project professionals, organizations and the ID project body of knowledge. The study can be extended to analyse other developing country projects sponsored by different donors.
Description:
This paper presents an investigative study in which data were gathered and used in underground mining to improve the planned maintenance program and reliability of the shearer loader in the underground mining. A cost effective maintenance and operation strategy and practices is mandatory to meet the production demand and the required level of service of this critical asset of the plant. The study conducted and presented in this paper includes a detailed review of failure history data and the use of analytical technique available to understand failure characteristics and its effect on the throughput and the overall performance of the longwall operation. This is to achieve further productivity increases to meet business goals. Analytical tools such as Failure Mode and Effect and Criticality Analysis (FMECA) and Weibull analysis were used in this investigation. The study has highlighted the criticality of some failures and the actions needed in this industrial case to improve the reliability and planned maintenance for a better mining productivity.
Description:
Flexible operation of post-combustion CO2 capture (PCC) plants can improve efficiency through coordinating the balance between consumer demands for electricity and CO2 emission reductions. This strategy however, will impose process disturbances while the PCC plant is ramped up, ramped down or turned off. This paper presents the preliminary development of a dynamic model for PCC in a brown coal-fired power plant using the process simulation software Aspen Plus Dynamics. Validation of the dynamic model will be against both steady state and dynamic data from the pilot plant. By gaining this understanding of the dynamic behavior, the technical and financial performance of PCC can be optimised.
Description:
Flexible operation of post-combustion CO2 capture (PCC) plants can improve efficiency through coordinating the balance between consumer demands for electricity and CO2 emission reductions. This strategy however, will impose process disturbances while the PCC plant is ramped up, ramped down or turned off. This paper presents the preliminary development of a dynamic model for PCC in a brown coal-fired power plant using the process simulation software Aspen Plus Dynamics. Validation of the dynamic model will be against both steady state and dynamic data from the pilot plant. By gaining this understanding of the dynamic behavior, the technical and financial performance of PCC can be optimised.
Description:
Flexible operation of post-combustion CO2 capture (PCC) plants can improve efficiency through coordinating the balance between consumer demands for electricity and CO2 emission reductions. This strategy however, will impose process disturbances and the immediate and long term impact is unclear. There is a justified need for the development of accurate dynamic PCC models, as well as practical experience in dynamic operation of PCC pilot plants. This paper presents CSIRO PCC pilot plant data from the 2012 and 2013 dynamic campaigns using MEA solvent. The step-change approach to dynamic plant operation was implemented and the use of density meters to instantaneously measure CO2 loading instantaneously was investigated.
Description:
Flexible operation of post-combustion CO2 capture (PCC) plants can improve efficiency through coordinating the balance between consumer demands for electricity and CO2 emission reductions. This strategy however, will impose process disturbances and the immediate and long term impact is unclear. There is a justified need for the development of accurate dynamic PCC models, as well as practical experience in dynamic operation of PCC pilot plants. This paper presents CSIRO PCC pilot plant data from the 2012 and 2013 dynamic campaigns using MEA solvent. The step-change approach to dynamic plant operation was implemented and the use of density meters to instantaneously measure CO2 loading instantaneously was investigated.
Description:
Flexible operation has the potehtial to significantly improve the economic viability of post-combustion CO2 capture (PCC). However, the impact of disturbances from flexible operation of the PCC process is unclear. The purpose of this study was to investigate the effects of flexible operation in a PCC pilot plant by implementing step-changes for improved dynamic data reliability. The flexible operation campaign was conducted at the CSIRO PCC pilot plant at AGL Loy Yang using monoethanolamine (MEA) absorbent. The pilot plant was operated under a broad range of transient conditions (changing flue gas flow, liquid absorbent flow and steam pressure) to capture the dynamics of a PCC process during flexible operation. The study demonstrated that the dynamics of flue gas flow rate was faster than absorbent flow rate. The greatest CO2 removal% was achieved at the lowest flue gas flow rate or at the highest absorbent flow rate; however, the latter provided improved energy efficiency. The steam pressure parameter could adjust the temperature of all columns simultaneously which can be used to compensate for effects from ambient conditions or heat losses. These results verify the technical feasibility of flexible PCC operation and provide a suitable dataset for dynamic model validation. (C) 2015 Elsevier Ltd. All rights reserved.
Description:
Flexible operation has the potehtial to significantly improve the economic viability of post-combustion CO2 capture (PCC). However, the impact of disturbances from flexible operation of the PCC process is unclear. The purpose of this study was to investigate the effects of flexible operation in a PCC pilot plant by implementing step-changes for improved dynamic data reliability. The flexible operation campaign was conducted at the CSIRO PCC pilot plant at AGL Loy Yang using monoethanolamine (MEA) absorbent. The pilot plant was operated under a broad range of transient conditions (changing flue gas flow, liquid absorbent flow and steam pressure) to capture the dynamics of a PCC process during flexible operation. The study demonstrated that the dynamics of flue gas flow rate was faster than absorbent flow rate. The greatest CO2 removal% was achieved at the lowest flue gas flow rate or at the highest absorbent flow rate; however, the latter provided improved energy efficiency. The steam pressure parameter could adjust the temperature of all columns simultaneously which can be used to compensate for effects from ambient conditions or heat losses. These results verify the technical feasibility of flexible PCC operation and provide a suitable dataset for dynamic model validation. (C) 2015 Elsevier Ltd. All rights reserved.
Description:
Overall Equipment Effectiveness (OEE) evaluates quantitatively how effectively a manufacturing operation is utilised. Total Productive Maintenance (TPM) was considered by Tibaldi, a leading food manufacturer in Australia for achieving OEE. This research project has identified performance gaps, developed plan and implemented it in Thermoforming area of the business. The developed methodology helped Tibaldi in improving productivity and quality through TPM involving machines, equipment, processes, and employees. This paper demonstrates how this can be achieved by reducing lead time and establishing lean environment. Productivity improvement through the devised methodology led to further enhancement of competitiveness of the organisation for domestic and international markets of processed food manufactured by Tibaldi Australia. Lessons learned from application of TPM in Thermoforming, a key asset area, is rolled out to other sections of the plat and results from this pilot study are presented in this paper.
Description:
Overall Equipment Effectiveness (OEE) evaluates quantitatively how effectively a manufacturing operation is utilised. Total Productive Maintenance (TPM) was considered by Tibaldi, a leading food manufacturer in Australia for achieving OEE. This research project has identified performance gaps, developed plan and implemented it in Thermoforming area of the business. The developed methodology helped Tibaldi in improving productivity and quality through TPM involving machines, equipment, processes, and employees. This paper demonstrates how this can be achieved by reducing lead time and establishing lean environment. Productivity improvement through the devised methodology led to further enhancement of competitiveness of the organisation for domestic and international markets of processed food manufactured by Tibaldi Australia. Lessons learned from application of TPM in Thermoforming, a key asset area, is rolled out to other sections of the plat and results from this pilot study are presented in this paper.
Description:
A total of 4% of availability increase was achieved in an Iron Ore Train Unloader facility. A Six Sigma approach, supported by statistical techniques such as Pareto and Jackknife, is used to identify the main causes of loss and implement corrective actions, based on repetitive data collected within the time usage model accounting system. A classification method was utilised to separate production delays into different categories and target the focus of the defect elimination program in a staged approach. Via root cause analysis and fishbone diagrams, effective defect elimination tasks are identified to eliminate process outliers. Prioritisation tools and effective resource allocation are utilised to achieve an increased value adding defect elimination strategy. A control process of ongoing monitoring and data analysis is implemented to maintain sustainability of the program throughout the lifecycle of the asset and continuously improve availability. A total of 3.3 Mt of increased iron ore productivity within the Iron Ore Train Unloader facility was the result observed in the last 12 months.
Description:
Generally, an industrial robot is named the Single-Function Robot (SFR) if it is only able to perform one task like material handling. However, a Multi-Function Robot (MFR) predominantly performs two tasks concurrently: material handling and a special operation. This type of recent robot with this ability can raise production rate. A robot equipped by a special kind of gripper namely Grip-Gage-Go is a real-life applications of MFRs. This gripper makes MFR competent to measure the diameter of the part in transit. These MFRs are widely employed in the inspection of automotive products including crankshaft, gears, and engine valves [1]
Description:
This paper investigates the scheduling of a rotationally arranged robotic cell with the Multi-Function Robot (MFR). The earlier known robotic study in this area assumed that the robot only moves the part between machines. We lift this assumption on robot tasks and assumed a special class of robots which is also able to perform a special operation in transit. The aim is to find a minimum cycle time for identical part production. Considering additive and constant travel-time, the distance between any two machines is varying or constant based on the robot acceleration/deceleration for incompact and compact cells. The lower bound of the cycle time is deduced to evaluate the optimality of two practical permutations namely uphill and downhill. It also identifies the regions where using a Multi-Function Robotic Cell (MFRC) is more economical than a Single-Function Robotic Cell (SFRC).
Description:
This study is focused on the domain of a two-machine robotic cell scheduling problem. Particularly, we propose the first analytical method for minimizing the partial cycle time of such a cell with a PC-based automatic inspection system to make the problem more realistic. It is assumed that parts must be inspected in one of the production machines, and this may result in a rework process. The stochastic nature of the rework process prevents us from applying existing deterministic solution methods for the scheduling problem. This study aims to develop an in-line inspection of identical parts using multiple contact/non-contact sensors. Initially, we present a heuristic method that converts a multiple-sensor inspection system into a single-sensor inspection system. Then, the expected sequence times of two different cycles are derived based on a geometric distribution, and finally the maximum expected throughput is pursued for each individual case.
Description:
This paper introduces a new methodology to optimise the cycle time of dual-gripper robotic workcells. The workcell under study is composed of a group of m production machines. In order to produce a completed part, a chain of m-1 secondary operations are performed by m-1 different machines, and a hub machine is alternately visited for m primary operations. Indeed, parts must reenter the hub machine after any one of secondary operations. Those types of robotics workcells are used for high capacity production such as in photolithography manufacturing, These cells are cluster tools for semiconductor manufacturing where a wafer visits a processing stage several times for the atomic layer deposition (ALD) processes. For electroplating lines, these cells are also common in practice where there is a multifunction production stage that is visited by parts over once. This optimisation methodology is limited to the dual-gripper robotic cells, where identical parts are produced and these parts completely follow a similar sequence. The lower bound of cycle time for such dual-gripper robotic cells is obtained by finding the cycle time of all related robot move cycles, and subsequently optimal robot task sequence, which is a two-unit cycle, is determined.
Description:
Automated material handling systems are usually characterised by robotic cells that result in the improvement of the production rate. The main purpose of this research is to study the scheduling of a rotationally arranged robotic cell with the multi-function robot (MFR). This special class of industrial robot is able not only to transfer the part between two adjacent processing stages but also to perform a special operation in transit. Considering MFR for material handling and operation, the objective function of the research here is the maximisation of production rate, or equivalently the minimization of the steady-state cycle time for identical part production. This problem is modelled as a travelling salesman problem to give computational benefits with respect to the existing solution methods. Then, the lower bound for the cycle time is deduced in order to measure the productivity gain of two practical production permutations, namely uphill and downhill permutations. As a design problem, a preliminary analysis initially identifies the regions where the productivity gain of a regular multi-function robotic cell is more than that of the corresponding single-function robotic cell for both small- and large-scale cells. The conclusion shows the suggested topics for future research.
Description:
The phenomenon of deadlock in robotic cells has been long ignored by most scheduling literature. A deadlock situation arises if a part cannot change its current state indefinitely since the destination machine is occupied by another part. The probability of the deadlock occurrence is likely to be large when the processing route cannot be predicted with certainty due to inspection processes. Our focus here is on a specific robotic cell with a post-process inspection system where the inspection is performed on an independent inspection machine. Avoidance and recovery policies are applied to overcome deadlocks originated from this cell. We develop these policies to prevent deadlock or alternatively resolve it during the online implementation of cycles. The former policy minimizes the storage cost, whereas the later policy minimizes the expected cycle time. An analysis of the scheduling problem that involves timings and costs is also carried out for comparing policies.
Description:
The industrial robot is one of the popular devices used in fully automatic production lines as material handling tool. A consequential problem is finding a cyclic robot movement which gives the maximum cell output in mass production environments. The Robotic Cell Scheduling Problem (RCSP) is predominantly separated into two different problems: Single-Function Robotic Cell (SFRC) and Multi-Function Robotic Cell (MFRC) scheduling problem. These problems are layout-oriented and operation-oriented, respectively. Literature concerning with former case considered a robotic system served by a transporting robot performing a single task. This kind of transporting robot is usually called Single-Function Robot (SFR). For the latter case, the robotic system served by a Multi-Function Robot (MFR) which simultaneously perform an arbitrary task in addition to parts transportation task. Giving a real-life example of MFRs, the use of a class of grippers performing in-process control is significantly increased in industry. The grippers, install at the end of MFR arm, can perform quality control tasks (e.g. accurately measure diameters) while part is carried to next machine. Figure 1 shows an example of these grippers used for measuring the diameter of crankshaft [1]. The measuring heads are integrated into the automation by adding gages and crankshaft locating features to MFR using in these lines. Also, there is a special kind of MFR, namely SDA10, which is suitable for assembly and part transfer in production lines especially if fixturing is costly [2]. Thus, it is crucial to undertake a comprehensive research onto effect of MFRs on production rate.
Description:
This paper addresses the problem of finding the optimal robot move cycle to minimise the cycle time of two-machine cells. The earlier robot's function was mainly moving parts between machines in a manufacturing process. We lift this assumption on robot tasks and assumed a special robot, namely multi-function, which performs a unique operation in transit. This robot starts performing this operation after unloading a part from input buffer and finishes it before loading the part to the output buffer. The processing mode on robot is “stop resume”. Thus, regardless of the gap interrupts during the operation, the robot continues processing on part when it is reloaded to the robot without any loss in time. The focus of this study is on one-unit cycles since they are very popular in industry. The cycle time of two possible one-unit cycles is obtained, and the optimality condition of them is determined.
Description:
This paper presents a case study on a reservoir simulation modeling of recycling gas condensate using Modified Black Oil formulation (MBO) to identify and recover the by-passed condensate in Al-Raja Field. Al-Raja field is a good candidate to utilize MBO formulation instead of fully compositional due to following reasons (1) Gas injection/recycling is able to maintain the reservoir pressure above or at the dew point pressure in Al-Raja Field. (2) by keeping reservoir pressure above dew point pressure, gas injection will prevent any Retrograde Liquid Deposit (RLD) occured in the reservoir. It was well accepted methodology that MBO can be used in lean to medium rich gas condensate reservoir under gas cycling above dew point. Al-Raja field is located in the Eastern part of the Marib-AlJawf Basin Republic of Yemen. The field has a moderate-size medium rich gas condensate reservoir with an average gas production rate of 750 MMscf/D from 18 wells. The lean gas is being re-injected back into the reservoir using line-drive pattern wells. Some make up gas from nearby fields was provided to replace fuel and shrinkage volumes. The high vertical relief of the field structure leads to significant temperature gradient that resulted in challenges to model the oil-gas ratio (Rv). The primary objective of the study is (1) to evaluate the current gas recycling performance at well and field level, (2) identify the location of current by-passed condensate (3) utilize the model to improve and optimize the liquid recovery through several options of optimum field developments (infill wells). To achieve the objectives, 3-D Static and Dynamic models with 4 components MBO definition were constructed. In this study, we will show how to generate PVT Modified Black Oil (MBO) properties such as solution gas-oil ratio (Rs), oil-gas ratio (Rv), oil formation volume factor (Bo), and gas formation factor (Bg), from PVT-EOS. Whitson and Torp procedures were selected to calculate MBO properties from PVT experimental data of gas condensate. The use of the MBO approach enabled us to perform faster field performance history matching compared with the compositional. This approach preserves less run time to conduct the Al-Raja prediction including infill drilling optimization. The condensate-gas ratio distribution achieved after the history match process guided us to locate the optimum infill well locations in by-passed area for the future development. Moderate condensate areas were located, and several wells have been drilled and proved to be successful. More infill wells were recommended to raise the field production and recover the remaining reserve.