Archive for category Knowledge Area
Reducing Cost of Road Maintenance for the Resources Industry
Posted by systems in Lean and Green Operations, News, Optimization, Research Area, Research Highlights, Technical Area on 24/04/2018
Haul road in open mine has short durability. It is because haul road is constructed without asphalt/concrete pavement and passed by big vehicle with heavy load. There is some kind of decreasing quality of haul road such as improper cross section, inadequate roadside drainage, corrugations, potholes, ruts, and loose aggregate. Poor haul road quality will impact on increasing production costs and decreasing mine productivity. Usually open mine use motor grader to maintain the quality of haul road. Way of working of motor grader is to scrap the inadequate haul road surface.
There are some differences among the haul road segments such as characteristic, traffic density, kind of decreasing quality, durability, etc. Therefore, systematically grader route and schedule is needed to minimize the delay of haul road maintenance. Usually grader route and schedule just based on grader’s operator experience. There is no specific approach that can be used in grader route and schedule.
This research focused on grader route and schedule optimization in coal haul road maintenance. Optimization model in this research is designed using Bandit Algorithm. The objective of the optimization model is to minimize the maximum penalty. In this case, penalty is used to describe amount of loss that is caused by maintenance delay on each haul road segment. Grader start from the initial point to a road segment and moves over and over to the other road segment until working hour is over. Determination of he next road segment is based on weight of maintenance delay on each road segment. Greater the weight of the maintenance delay of a road segment, greater the probability of that road segment to be addressed by grader. Grader scraps if the road segment is late maintained and just passes if otherwise. When the working hour is over, grader stops moving and optimization model calculates the objective and records the route as a new solution. The steps are done again as many as have been determined (iteration). Solution with the best objective is chosen as the final solution.
With the probability, grader is not directly addressed to the road segment with the greatest maintenance delay weight to allow for the other road segments to be the next grader destination. This is because short term solutions have effect on long-term solution (whole solution); maybe the best short-term solution is not the best long-term solution. An example in a simpler problem is: we must determine route from city A to city D with 2 possible route that are A-B-D and A-C-D. With the distance between A-B < A-C, A-B is the best first movement. But for the overall movement, maybe A-B-D is not the closest route. Although the distance between A-B < A-C, distance of A-C and C-D can be closer than A-B and B-D.
Optimization model showed a significant cost savings for the mining operations by creating a more effective roads maintenance with reduce cost. With the pressure of low prices in the resources industry, a simple but yet complex optimization can help them stay more competitive.
This research is conducted by Denni and Dr. Komarudin.
Can Biodiesel Industry achieve its target by 2025: an Agent Based Model Exploration
Posted by systems in Agent Based Modeling, Clean and Renewable Energy, Knowledge Area, News, Research Area, Research Highlights, Technical Area on 15/03/2018
“Change is easy to purpose, hard to implement and especially hard to sustain”
-Andy Hargreaves
As we know, biodiesel or Fatty Acid Methyl Ester (FAME) is one type of biofuel produced as a substitution of diesel fuel. In Indonesia, biodiesel is produced using crude palm oil by trans-esterification process. The usage of crude palm oil is performed because it sees that Indonesia is a nation with the biggest yield of crude palm oil in the Earth. In summation to the potential of its natural resources, the role of biodiesel as a substitute of diesel fuel is caused because it considers the benefits generated by biodiesel itself. Benefits include the so-called “carbon neutral”, the fuel produced biodiesel does not raise the output of carbon dioxide (CO2). The issue occurs because when the oil crop grows, it absorbs CO2 at the same amount as releasing fuel. In addition, biodiesel has biodegradable compounds that are firm and completely non-toxic, having in mind that biodiesel spills have less risk than diesel fuel. Biodiesel also has a higher flash point than diesel fuel, can be determined from its higher cetane value (> 57) than diesel fuel.
Still, the condition of biodiesel production in Indonesia faces complex problems. The concentration of biodiesel has never been fully attained, with the concentration of non-subsidized biodiesel that has not been carried out optimally. There are four major problems facing biodiesel production. Firstly, the concentration of biodiesel production is not maximal, especially in non-subsidized biodiesel production. Second, the condition of Indonesia’s domestic biodiesel production that began to decline from 2014 to 2015 due to lower oil costs. Tierce, the number of business entities that are abundant, but relatively small to fulfill the objective of production capability in 2025 amounted to 10.22 million KL. And the last and most important is the increasing CPO price, condition that causes the Biodiesel Market Index Price to be less frugal. This problem becomes the consideration of the biodiesel industry to continue to sell its biodiesel in Indonesia.
To avoid such problems, agent-based modeling can be used to predict the impact of policies on influential actors to gain a deep understanding of the behavior and decisions made by the biodiesel industry by looking at the types of biodiesel industry in Indonesia that are differentiated by the type of production capacity that can be handled by the biodiesel industry, decision-making that depends on the type of industry, how the biodiesel industry calculates the expenditure and income as well as the learning gained by the biodiesel industry after large-scale production. This agent-based modeling is done with two policy alternatives, namely price determination of biodiesel market index and subsidy of installed capacity of the biodiesel plant.
The results obtained from this agent-based modeling show that the policy of adding the biodiesel plant installed capacity has a good impact in increasing the fulfillment of biodiesel production, the adoption and competition that occurs in the tender, and the profits gained by the biodiesel industry. Even so, the government should count the costs to be incurred and the net income from biodiesel industry, so the biodiesel production targets can be successfully accomplished.
This research is conducted by Vicky Larasvasti Respati and Akhmad Hidayatno
This is What You Should Do When You Have No Doraemon’s Magical-Anywhere-Door
Posted by systems in Knowledge Area, Optimization, Ports, Logistics and Supply Chain, Research Area, Technical Area on 10/01/2018
There are times when we wish Doraemon’s magical-anywhere-door really does exist. If so, we can reach our destination without having to travel miles in a long time. But, since Doraemon does not exist, fortunately there is something we can do to at least save the mileage and time we sacrificed to travel from one to another places. Especially in case of post men or delivery couriers who have to visit a lot of destinations in such limited amount of time and capability.
Recently, a research assistant from Systems Engineering, Modeling, and Simulation Laboratory from Industrial Engineering major, Universitas Indonesia is conducting a research about Vehicle Routing Problem with Time Windows to optimize distribution route and schedule. It was first inspired by Indonesia’s current logistic condition which is still not optimal. It is proven by the decreasing index of Indonesia’s logistic performance during the past five years. One of the reason is the high Indonesia’s logistic cost which can be considered as the highest logistic cost in the world. And the one that contributes almost half of the logistic cost is transportation cost.
On the other side, customer needs are rising annually. Moreover, the growing online shopping market create an increasing demand of same-day delivery service. Based on McKinsey survey, online retailers as the main originator of B2C shipments, have a large interest to reduce delivery time in order to foster the products sale. Therefore, we need a better planning of distribution route and schedule, especially for delivery service providers and courier companies.
The purpose of research conducted at SEMS Laboratory about Vehicle Routing Problem with Time Windows (VRPTW) is to find the most optimum distribution route with lowest total distance yet still manage to fulfill all demand and considering the constraints of vehicle capacity and customers’ time windows.
Since VRPTW belongs to NP-hard optimization problems, our researcher used heuristic method which is translated to Netbeans 8.1 software in C++ programming language. They also use local search to perform simple iterations to produce fairly accurate solutions. Local search methods which are used in this study are exchange, two-opt, and insert. They can be applied to customers in the same route (intra-route) and customers in different routes (inter-route). Basically, these methods perform some iterations of moves that determine the most optimum combination and sequence of customers to visit. This will be finalized by using Lin Kernighan Helsgaun algorithm. The iteration will stop once it can not generate a better solution.
Fig 1. Illustration of 2-opt intra-route move
The resulting improvements will ultimately result in reduced transportation costs. Thus, vehicle routing problem with time windows can be a solution for urban logistic problems. So, when you do not have any Doraemon’s magical door, make yourself sure that at least you have a well-planned distribution route and schedule!
This Research is Conducted by Vincencia Sydneyta and Dr. Komarudin
How Should Indonesia Manage Their Transition to Cleaner Energy Consumption? Reflecting Back
Posted by systems in Clean and Renewable Energy, Continuous Event Modeling, Knowledge Area, News, Research Area, Research Highlights, Technical Area on 29/12/2017
The threat of fossil energy scarcity due to massive usage over the last few years and the harm of fossil energy to the environment has prompted countries to consider energy transition to their alternative energy (cleaner and renewable energy), to keep the balance of their environment system. Including Indonesia, where 60% of their energy consumption since 2000 lean on the fossil energy, especially in oil energy. Indonesia’s oil consumption has been higher than its consumption since 2004, which cause Indonesia’s to import tons of barrel of oil every year. The crisis of Indonesia’s energy consumption rises when in 2008, global oil prices increase rapidly which shaken most of the world’s energy and economic system.
To handle the crisis, Indonesia since 2007 has successfully executed an energy transition program, named “Conversion Program from Kerosene to LPG (Liquefied Petroleum Gas)” which targeted household and small business consumption. The program has managed to increase the LPG consumption and reduce energy subsidies by 197 million rupiahs by 2012. This program is highlighted since Indonesia has not yet considered being successful in executing similar programs, which is the conversion program from petrol to gas fuel for road transportation.
In the future, Indonesia will be facing lot more transition program, to the cleaner and renewable energy, as can be seen on Indonesia energy mix. This indicates the needs to evaluate the successful and the unsuccessful system of the implemented energy transition program in Indonesia.
SEMS aim to explore the government policy structure which believed has a strong role to support or block people adoption on the conversion program of kerosene to LPG. Using System Dynamic Modelling, researchers propose to design a model which describe the system of conversion program and analyze the interactions among variables within the system of the successful conversion program. Furthermore, the analysis of the research also comparing government policy structure between the successful and the unsuccessful program.
The simulation of system dynamic shows that from the sets of policy intervention on the conversion program kerosene to LPG, kerosene supply withdrawal and the government push to increase production capacity of supporting equipment has a huge influence to support the energy transition program. From the comparison between the successful and the unsuccessful conversion program in Indonesia, researchers can indicate some differences. However, the most importance policy intervention in conversion program of kerosene to LPG, kerosene withdrawal and government push to increase production capacity of supporting equipment, has not yet implemented in conversion program from petrol to gas fuel to for road transportation.
This research is conducted by Theresa Devina and Akhmad Hidayatno
How to optimize unequal area facility layout to maximize storage
Posted by systems in Knowledge Area, Lean and Green Operations, News, Optimization, Research Area, Research Highlights, Technical Area on 15/11/2017
Facility layout problem, especially with the unequal departmental area (UAFLP), is one of the problems studied in combinatorial optimization and has received the attention of many researchers in the past decade. The goal of UAFLP is to allocate departments into a facility to obtain the most efficient arrangement. The UAFLP study has a final objective to minimize the total cost of material handling between departments.
Competition in today’s business world is inevitable. Increasing the quality of productivity becomes one of the keys to success in facing competition with business management effectively and efficiently. This can happen by maximizing existing resources ie employees, machines, and other facilities. Therefore, the industry needs to be able to optimize production capability and effectiveness to face competitors. The production process becomes the key that needs to be managed effectively to minimize production costs with higher effectiveness.
Facility layout design has a close reinforcement to the size of the physical arrangement of elements in a manufacturing and service system, such as department, machinery, operational tools, and so on. The purpose of the facility layout design is the design with the minimum material handling cost. With proper facility layout, material handling costs can be reduced. In general, material handling contributes about 20-50 percent of the total. Reduction in the company’s operational costs, along with the increased efficiency of the production system becomes a necessity that every industry needs to do.
The problem of facilities layout that is often the researcher’s attention is Unequal Area Facility Layout Problem (UAFLP). Initially, UA-FLP was developed by Armor and Buffa (1963). They explain that there is a rectangular facility with a fixed Width and Height and several (n) departments that need to be allocated to the facility. There are some problems that have not found the optimal solution and require a long computation time. The goal is to reduce non-feasible solutions to reduce the complexity of possible solutions.
This research will develop a mathematical model using Mixed Integer Programming method based on Flexible Bay Structure. Some additional constraint functions will be attempted to be added to the model. Testing is done by comparing the effect of each additional constraint function that has different approaches in cutting the complexity of possible solutions. The comparison result of the combination of the constraint function used indicates which constraint function has a major influence in reducing the computation time of the model.
This research concludes that all simulated problem sets using additional constraints in the model can provide better computation time than before. The effect that occurs can be the value of the solution becomes not optimum or remain optimum. All computational time gives significant improvement.
This research is conducted by Randa Adi Saputra and Komaruddin
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