Penerapan Six Sigma Untuk Perbaikan Masalah Kepadatan Dan Kemacetan Workstation Gudang Ekspor Di Perusahaan Cargo Handling Bandara Soekarno Hatta

Pengangkutan kargo melalui pesawat udara merupakan salah satu rantai distribusi barang yang memerlukan biaya dan juga standar keselamatan yang tinggi. PT Jasa Angkasa Semesta (JAS) merupakan salah satu perusahaan ground handling di Bandara Internasional Soekarno Hatta yang salah satu unit usahanya adalah penanganan kargo di gudang ekspor. Salah satu proses di gudang ekspor adalah proses menaikkan kargo ke dalam Unit Load Device (ULD) atau biasa disebut proses build up yang dilakukan di workstation. Kepadatan dan kemacetan sering terjadi di workstation dan akibatnya proses build up, proses penimbangan, pelaporan dan penarikan kargo ke pesawat menjadi terhambat. Penelitian terhadap kepadatan dan kemacetan di workstation bertujuan untuk memecahkan masalah di workstation. Penelitian ini menggunakan metode six sigma DMAIC (Define, Measure, Analyze, Improve dan Control) untuk memecahkan masalah. Dalam tahap define dimulai dengan membuat project charter dan menentukan tim yang akan terlibat. Pada tahap measure menunjukkan bahwa level sigma pada workstation berada pada σ = 3.18. Analisis dilakukan dengan menggunakan metode fishbone dan menunjukkan bahwa penyebab utama dari masalah kepadatan dan kemacetan adalah kapasitas workstation dan penjadwalan build up. Untuk tahap improvement dilakukan dengan melakukan brain storming untuk melakukan perbaikan dan control dilakukan untuk memastikan bahwa improvement yang dibuat akan selalu sesuai harapan. Hasil penerapan penjadwalan, dengan perbandingan hari ke hari, kepadatan dapat berkurang sebesar 28% dan hasil perbaikan penurunan defect sebesar 8.7%. ======================================================================================================== Air cargo transportation is one of goods distribution with high cost and high safety standard. PT Jasa Angkasa Semesta (JAS) is one of ground handling company in Soekarno Hatta International Airport where one of its businesses is cargo handling in export warehouse. One of the processes in the export warehouse is loading cargo into Unit Load Device (ULD) or build up in the workstation. Bottleneck often occurs in the workstation and it affects the build up process, weighing process, reporting, and cargo towing to the aircraft is late. The research was aiming to solve the problem in the workstation. The research used six Sigma DMAIC (Define, Measure, Analyze, Improve, and Control) methodologies to solve the problem. The define phase roll out the project charter and the team involved. On the measure phase reveals that the sigma level of the workstation was on σ = 3.18. The analysis was conducted using fishbone method and the main causes of the bottleneck were capacity and build up scheduling. On improve phase, brain storming was carried out to solve the issue and capability analysis was made to make sure no recurrence on suggested improvement. The result of Build up scheduling implementation reduced congestion by 28% and yield improvement 8.7%

ÇKKV ve Tamsayılı Programlama Yöntemleri ile Bir Üretim İşletmesinde Uzaktan Çalışma Modelinin Oluşturulması

Tüm dünyada etkisini sürdüren Covid-19, iş hayatında çalışma koşullarının değişmesinde büyük rol oynamıştır. Covid-19’un ortaya çıkmasından sonra birçok işletme uygun bir bilgi işlem altyapısı varsa uzaktan çalışma ya da dönüşümlü çalışma modeline geçmeyi tercih etmişlerdir. Bilgi işlem altyapısı eksik olan işletmeler ise altyapılarını geliştirmeye ve uzaktan çalışma modeline geçmek için gerekli şartları sağlamaya çalışmıştır. Bu süreçte ofiste bulunan çalışan sayısının azaltılması ve temasın mümkün olduğunca azaltılabilmesi açısından uzaktan çalışma modeli bir ihtiyaç haline gelmiştir. Bu çalışmada, Denizli’de faaliyet gösteren bir üretim işletmesinde, ofiste bulunan çalışan sayısını azaltmak amacıyla öncelikle uzaktan çalışmaya uygunluğa yönelik kriterlerin ağırlıkları MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique) yöntemiyle belirlenmiş, sonrasında TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) yöntemi ile çalışanlar uzaktan çalışma modeline uygunluğa göre sıralanmış ve işletmenin uzaktan çalışma modeline göre belirlediği kurallar dikkate alınarak tamsayılı programlama yöntemi ile çalışanların uzaktan çalışma ve ofisten çalışmasına yönelik dönüşümlü çalışma modeli oluşturulmuştur. Bu çalışmada önerilen yöntemler yardımıyla, manuel olarak oluşturulan çizelgelere göre daha adil ve işveren taleplerini karşılayan bir çalışma modeli oluşturulmuştur

Improving demand forecasting in the air cargo handling industry: A case study

Air transportation plays a crucial role in the agile and dynamic environment of contemporary supply chains. This industry is characterized by high air cargo demand uncertainty, making forecasting extremely challenging. An in-depth case-study has been undertaken in order to explore and untangle the factors influencing demand forecasting and consequently to improve the operational performance of an Air Cargo Handling Company. It has been identified that in practice, the demand forecasting process does not provide the necessary level of accuracy, to effectively cope with the high demand uncertainty. This has a negative impact on a whole range of air cargo operations, but especially on the management of the workforce, which is the most expensive resource in the air cargo handling industry. Besides forecast inaccuracy, a range of additional hidden factors that affect operations management have been identified. A number of recommendations have been made to improve demand forecasting and workforce management

Improving demand forecasting in the air cargo handling industry: A case study

Air transportation plays a crucial role in the agile and dynamic environment of contemporary supply chains. This industry is characterized by high air cargo demand uncertainty, making forecasting extremely challenging. An in-depth case-study has been undertaken in order to explore and untangle the factors influencing demand forecasting and consequently to improve the operational performance of an Air Cargo Handling Company. It has been identified that in practice, the demand forecasting process does not provide the necessary level of accuracy, to effectively cope with the high demand uncertainty. This has a negative impact on a whole range of air cargo operations, but especially on the management of the workforce, which is the most expensive resource in the air cargo handling industry. Besides forecast inaccuracy, a range of additional hidden factors that affect operations management have been identified. A number of recommendations have been made to improve demand forecasting and workforce management

Modeling and Analysis of Aerial Port Operations

The focus of this thesis effort is gaining useful insight into aerial port operations by employing an animated simulation. Understanding airfield capacity, resources, and functioning allows greater accuracy and efficiency in both planning for future force structures and matching mobility assets with commanders\u27 objectives. Two current simulations, ACE (Airfield Capacity Estimator) and BRACE (Base Resource Allocation and Capabilities Estimator), model mobility activities at the base level with some deficiencies. The model proposed by this thesis, APOM (Aerial Port Operations Model), will provide the mobility analyst an animated simulation with two, new measures of aerial port operations; a real-time estimate of airfield capacity subject to changing levels of airfield resources, and an instantaneous count of serviced aircraft (service MOG). Additionally, APOM will offer an expanded utility to the mobility analyst by modeling a ground transportation network associated with the aerial port

On the design of sparse but efficient structures in operations

It is widely believed that a little flexibility added at the right place can reap significant benefits for operations. Unfortunately, despite the extensive literature on this topic, we are not aware of any general methodology that can be used to guide managers in designing sparse (i.e., slightly flexible) and yet efficient operations. We address this issue using a distributionally robust approach to model the performance of a stochastic system under different process structures. We use the dual prices obtained from a related conic program to guide managers in the design process. This leads to a general solution methodology for the construction of efficient sparse structures for several classes of operational problems. Our approach can be used to design simple yet efficient structures for workforce deployment and for any level of sparsity requirement, to respond to deviations and disruptions in the operational environment. Furthermore, in the case of the classical process flexibility problem, our methodology can recover the k-chain structures that are known to be extremely efficient for this type of problem when the system is balanced and symmetric. We can also obtain the analog of 2-chain for nonsymmetrical system using this methodology. This paper was accepted by Yinyu Ye, optimization. </jats:p

Sustainability and Economics of Aviation Industry

Aviation draws people attention, not only because it is a dream of human race to fly or the association to vacations, but its role in our modern economies. It is, first of all, an incredible investment, such as building airports, buying aircrafts, lands, control systems…etc. There are great business opportunities as well as risks. Moreover, the operation of airports, airlines or aircraft manufacturing generate tremendous incomes and jobs, often vital to cities heavily relay on these business. Furthermore, politic issues, such as regulations, agreements, ownerships and business decisions in company level, are shaping the market. Last but not least, enhanced by aviation, the connectivity and attractiveness of city induce economic benefit in tourism, business and so on, are very seductive to governors hoping to exploit its economic potential. However, just like any aspect of economics, there are externalities, which is not always captured nor considered by decision makers. Externality is always the first question I ask. To quantify and internalize them will enhance market efficiency and the fairness of society. Furthermore, the trend and abnormality are crucial in this uncertain world if we want to predict the future. Focusing on econometrics, i.e. applying statistical tools on economic data to spot estimators and to set models, reference points for discussion or decision could be provided while arousing the awareness of less-acknowledged matters by including them in the models. Three papers are presented in this report. First of all, as the fastest growing transport mode, aviation sustainability and environmental costs are generally concerned. We tried to address the noise and emission of the global aircraft fleet and to argue the current technology progress is not vigorous enough, while examining the trade off of these externalities. We find a statistically significant impact of incremental technical progress on all environmental externalities. Substantial innovation is found to have positive effect on per-passenger externalities. These results point to the need for incentives in aviation technical progress. Secondly, the blooming of passenger traffic, particularly contributed by low cost airlines across Europe is shaping the air transport market, regulations and policies. By observing the carbon dioxide footprint of flights departing from Lombardy region, we find distinguished characteristics of LCC and also capture the impact of air traffic policies of government and airlines. we found that European non-environmental-oriented policies brought environmental benefits: Low cost carriers, their entrance as a consequence of liberalization, perform 18.24% to 24.50% better in terms of emission efficiency; Italian aviation policies (traffic distribution rule on Linate airport) have no significant effect while a drop of 2.61% CO2 level is observed, ceteris paribus, after the dehubbing of the national airline from Malpensa airport. We also confirm the annual improvement of aviation technology to be 1.9% while such effect is outweighed by the growth of traffic volume. Last but not least, air transport generates economic benefit to airlines, airports, local areas and countries. While the movement of people is well studied, we explore the benefit of movement of goods by air cargo, which is playing an essential role in new economies characterized by high-cost and time sensitive goods. We conclude that one percentage increase in total value export of good induces 0.47% increase in cargo volume. The marginal impact of an additional destination to cargo volume is 1.4%. We also provide evidence in the relationship of growth in air cargo volume with increasing online purchase in Europe.Aviation draws people attention, not only because it is a dream of human race to fly or the association to vacations, but its role in our modern economies. It is, first of all, an incredible investment, such as building airports, buying aircrafts, lands, control systems…etc. There are great business opportunities as well as risks. Moreover, the operation of airports, airlines or aircraft manufacturing generate tremendous incomes and jobs, often vital to cities heavily relay on these business. Furthermore, politic issues, such as regulations, agreements, ownerships and business decisions in company level, are shaping the market. Last but not least, enhanced by aviation, the connectivity and attractiveness of city induce economic benefit in tourism, business and so on, are very seductive to governors hoping to exploit its economic potential. However, just like any aspect of economics, there are externalities, which is not always captured nor considered by decision makers. Externality is always the first question I ask. To quantify and internalize them will enhance market efficiency and the fairness of society. Furthermore, the trend and abnormality are crucial in this uncertain world if we want to predict the future. Focusing on econometrics, i.e. applying statistical tools on economic data to spot estimators and to set models, reference points for discussion or decision could be provided while arousing the awareness of less-acknowledged matters by including them in the models. Three papers are presented in this report. First of all, as the fastest growing transport mode, aviation sustainability and environmental costs are generally concerned. We tried to address the noise and emission of the global aircraft fleet and to argue the current technology progress is not vigorous enough, while examining the trade off of these externalities. We find a statistically significant impact of incremental technical progress on all environmental externalities. Substantial innovation is found to have positive effect on per-passenger externalities. These results point to the need for incentives in aviation technical progress. Secondly, the blooming of passenger traffic, particularly contributed by low cost airlines across Europe is shaping the air transport market, regulations and policies. By observing the carbon dioxide footprint of flights departing from Lombardy region, we find distinguished characteristics of LCC and also capture the impact of air traffic policies of government and airlines. we found that European non-environmental-oriented policies brought environmental benefits: Low cost carriers, their entrance as a consequence of liberalization, perform 18.24% to 24.50% better in terms of emission efficiency; Italian aviation policies (traffic distribution rule on Linate airport) have no significant effect while a drop of 2.61% CO2 level is observed, ceteris paribus, after the dehubbing of the national airline from Malpensa airport. We also confirm the annual improvement of aviation technology to be 1.9% while such effect is outweighed by the growth of traffic volume. Last but not least, air transport generates economic benefit to airlines, airports, local areas and countries. While the movement of people is well studied, we explore the benefit of movement of goods by air cargo, which is playing an essential role in new economies characterized by high-cost and time sensitive goods. We conclude that one percentage increase in total value export of good induces 0.47% increase in cargo volume. The marginal impact of an additional destination to cargo volume is 1.4%. We also provide evidence in the relationship of growth in air cargo volume with increasing online purchase in Europe

The Air Cargo Load Planning Problem

A major operational planning problem in the air cargo industry is how to arrange cargo in an aircraft to fly safely and profitably. Therefore, a challenging planning puzzle has to be solved for each flight. Besides its complexity, the planning is mostly done manually today, which is a time consuming process with uncertain solution quality. The literature on loading problems in an air cargo context is scarce and the term is used ambiguously for different subproblems like selecting containers, packing items into containers, or loading containers into aircraft. All of the presented models only focus on certain aspects of what is in practice a larger planning problem. Additionally, some practical aspects have not been covered in the literature. In this work, we provide a comprehensive overview of the air cargo load planning problem as seen in the operational practice of our industrial partner. We formalize its requirements and the objectives of the respective stakeholders. Furthermore, we develop and evaluate suitable solution approaches. Therefore, we decompose the problem into four steps: aircraft configuration, build-up scheduling, air cargo palletization, and weight and balance. We solve these steps by employing mainly mixed-integer linear programming. Two subproblems are further decomposed by adding a rolling horizon planning approach and a Logic-based Benders Decomposition (LBBD). The actual three-dimensional packing problem is solved as a constraint program in the subproblem of the LBBD. We evaluated our approaches on instances containing 513 real and synthetic flights. The numerical results show that the developed approaches are suitable to automatically generate load plans for cargo flights. Compared to load plans from practice, we could achieve a 20 percent higher packing density and significantly reduce the handling effort in the air cargo terminal. The achieved costs of additional fuel burn due to aircraft imbalances and reloading operations at stop-over airports are almost negligible. The required runtimes range between 13 and 38 minutes per flight on standard hardware, which is acceptable for non-interactive planning. Cargo airlines can significantly profit from employing the developed approaches in their operational practice. More and especially the profitable last-minute cargo can be transported. Furthermore, the costs of load planning, handling effort, and aircraft operations can be significantly reduced

Improving the air cargo terminal operations through optimization

Ph.DDOCTOR OF PHILOSOPH

Optimization of transportation requirements in the deployment of military units

Cataloged from PDF version of article.We study the deployment planning problem (DPP) that may roughly be defined as the problem of the planning of the physical movement of military units, stationed at geographically dispersed locations, from their home bases to their designated destinations while obeying constraints on scheduling and routing issues as well as on the availability and use of various types of transportation assets that operate on a multimodal transportation network. The DPP is a large-scale real-world problem for which no analytical models are existent. In this study, we define the problem in detail and analyze it with respect to the academic literature. We propose three mixed integer programming models with the objectives of cost, lateness (the difference between the arrival time of a unit and its earliest allowable arrival time at its destination), and tardiness (the difference between the arrival time of a unit and its latest arrival time at its destination) minimization to solve the problem. The cost-minimization model minimizes total transportation cost of a deployment and is of use for investment decisions in transportation resources during peacetime and for deployment planning in cases where the operation is not imminent and there is enough time to do deliberate planning that takes costs into account. The lateness and tardiness minimization models are of min-max type and are of use when quick deployment is of utmost concern. The lateness minimization model is for cases when the given fleet of transportation assets is sufficient to deploy units within their allowable time windows and the tardiness minimization model is for cases when the given fleet is not sufficient. We propose a solution methodology for solving all three models. The solution methodology involves an effective use of relaxation and restriction that significantly speeds up a CPLEX-based branchand-bound. The solution times for intermediate sized problems are around one hour at maximum for cost and lateness minimization models and around two hours for the tardiness minimization model. Producing a suboptimal feasible solution based on trial and error methods for a problem of the same size takes about a week in the current practice in the Turkish Armed Forces. We also propose a heuristic that is essentially based on solving the models incrementally rather than at one step. Computational results show that the heuristic can be used to find good feasible solutions for the models. We conclude the study with comments on how to use the models in the realworld.Akgün, İbrahimPh.D