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Abstrak :
Agar dapat merespon permintaan pelanggan secara cepat perlu disiapkan sejumlah persediaan yang cukup besar, supaya tersedia pada saat dibutuhkan Penelitian ini mengembangkan model penjadwalan yang terdiri dari dua model. Model satu bertujuan melakukan penjadwalan untuk pemenuhan due date pada lingkungan Job Shop Paralel. Model dua bertujuan melakukan penjadwalan untuk penentuan due date. Pada sistem Job Shop Pararel dinamis yang memproses multi-item berstruktur multi-level, berdasarkan kinerja kualitas pada lingkungan produksi Just In Time (JIT). Pendekatan yang digunakan dalam penelitian ini adalah pendekatan mundur (backward approach) untuk pemenuhan due date dan pendekatan random untuk penentuan due date serta menggunakan metode Tabu Search dengan kriteria minimasi total actual flow time dengan memperhatikan tingkat cacat (defect rate) yang terjadi pada setiap tahapan proses yang dilalui. Peningkatan jumlah item dan jumlah level akan memberikan peningkatan jumlah alternatif jadwal yang berdampak pada CPU time yang diperlukan untuk mendapatkan solusi yang dapat memberikan total actual flow time yang minimum, namun dalam penelitian ini hanya terjadi untuk satu level multi item saja. Untuk dua level dan seterusnya tidak memberikan alternatif jadwal yang bervariasi untuk tingkatan item maupun level. Hal ini disebabkan karena inisialisasi solusi tetangga, panjang tabu list dan jumlah iterasi yang ditetapkan diawal membuat pencarian solusi berhenti di titik lokal optimum. ......In order to response the demand from customer quickly, it needs to have a large size of inventory. This research developes two scheduling model. The first models is to fulfill the due date in the paralel job shop manufacturing and the second is to make the due date itself. In the dynamic paralel job shop system which is produce the multi item structured by multi level, according to the quality performance in the just in time manufacturing. The research uses the backward approach to fulfill the due date and the random approach to make the due date using Tabu Search Method which objective is to minimize total actual flow time concern on defect rate. The increase of item and level affect the increase of scheduling alternatif and cpu time, but in this research it only happens for one level and multi item. For two level and so on it doesn?t give any varians scheduling alternative for level or item invrease. It might becuase of the inisialisasion of neighboor, the lenght of tabu list and iteration which made in the beginning and it makes the solution stop at the optimum local search.

Abstrak :
Penggunaan dispatching rule dalam menentukan urutan pengerjaan produk dalam flexible manufacturing system dapat memberikan solusi yang kurang baik apabila dispatching rule yang digunakan tidak sesuai. Pada tesis ini akan diperlihatkan perbandingan penggunaan beberapa dispatching rule baku dalam menentukan jadwal produksi, seperti First Come First Served (FCFS), Shortest Processing Time (SPT), Longest Processing Time (LPT), dan Earliest Due Date (EDD) serta sebuah usulan yang mempertimbangkan waktu terbuang untuk menunggu urutan pengerjaan produk pada mesin yang sama dalam waktu yang bersamaan dengan menggunakan alat bantu simulasi model. Pada tesis ini juga akan diciptakan model FMS dalam perangkat lunak, untuk kemudian disimulasikan menurut dispatching rules masing-masing, sehingga waktu penyelesaian masing-masing produk dan tardiness yang tercatat dalam hasil simulasi dapat dianalisa dan kemudian dibandingkan agar dapat dipilih untuk mendapatkan dispatching rules yang sesuai dan dapat memberikan kinerja yang paling baik. Perencanaan dispatching rule yang sesuai diharapkan dapat mempersingkat waktu penyelesaian tanpa melanggar tenggat waktu. Hasil yang didapatkan dalam penelitian ini menunjukkan bahwa dispatching rules yang sesuai merupakan kombinasi dispatching rule EDD dengan tetap mempertimbangkan waktu waktu terbuang untuk menunggu urutan pengerjaan produk pada mesin yang sama dalam waktu yang bersamaan melalui tenggat waktu minimum yang dimiliki masing-masing kombinasi urutan pengerjaan produk. ......Dispatching rules, which commonly used in determining job execution sequences, should be well planned in order to avoid bad solution caused by the usage of improper dispatching rules. In this thesis, the comparison of several dispatching rules is made to establish a compact production schedule on an FMS using a model simulation, such as First Come First Served (FCFS), Shortest Processing Time (SPT), Longest Processing Time (LPT), Earliest Due Date (EDD) and a proposal to consider the wasted time caused in waiting execution on a same machine at a same time. In this thesis, a model of FMS environment will be built on a software, and sequences which were produced on each dispatching rules, will be simulated based on the model created, for later the recorded value of completion time and tardiness of each product could be analyzed and compared further to gain a proper dispatching rule in giving the best performance. The proper dispatching rules planning will improve the completion time performance without violating the due dates. The result from the case on this thesis will show that the proper dispatching rule is a combination between EDD and the proposal of considering the wasted waiting time with the concern of minimum due dates attribute owned by each product execution.

Abstrak :
Penelitian ini, bertujuan mengembangkan model penentuan due date melalui penjadwalan batch untuk melakukan pemenuhan (Model 1) dan penentuan (Model 2) due date dengan mempertimbangkan defect rate. Pada sistem produksi job shop dinamis mesin parallel yang memproduksi muti-item berstruktur multilevel. Ukuran performansi yang digunakan yaitu total actual flow time. Proses penjadwalan dilakukan dengan menggunakan teknik penyisipan (insertion technique), yaitu melakukan penyisipan operasi-operasi disemua posisi pemproses yang mungkin pada semua mesin yang tersedia. Pemilihan posisi didasarkan pada kriteria tertentu dengan memperhatikan terpenuhinya semua urutan proses (routing) dan hubungan proses pendahulu yang ada diantara setiap operasi. Permasalahan yang diselesaikan dalam penelitian mencakup kondisi statis dan dinamis. ......This research, aims to develop due date determination model trough batch scheduling to accomplish the due date (Model 1) and due date assignment (Model 2) with defect rate consideration. On dynamic job shop machines parallel that produce multi- item structured multi-level. The measurement of performance used is the total actual flow time. Scheduling process is done by using the insertion technique, perform insertion operation at all position that may be available on all machine. The selection criteria are based on a specific criteria with respect to fulfillment of all the process sequence and predecssoe existing between each operation. The problem are solved in the static and dynamic conditions.

Abstrak :
PT. Pertamina (Persero) Lubricants merupakan unit bisnis PT. Pertamina (Persero) yang dikhususkan untuk memproduksi pelumas. Pelumas yang dihasilkan memiliki varian yang beragam sehingga biaya changeover yang terjadi bersifat sequence dependent. Permintaan produk pelumas yang fluktuatif mengakibatkan waktu penyelesaian produk melebihi due date yang telah ditentukan. Penelitian ini dilakukan untuk memperoleh penjadwalan produksi yang optimal dengan menggunakan model programa integer linier campuran yang diselesaikan dengan algoritma branch and bound. Dengan menggunaan bantuan pemrograman LINGO 9.0 versi extended, diperoleh penjadwalan produksi yang optimal dengan pengurangan biaya total produksi sebesar 29,76%.

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PT. Pertamina (Persero) Lubricants is PT. Pertamina (Persero)?s business unit which is specialized in lube oil production. The lube oil produced has many variants so the changeover cost occur has sequence dependent characteristic. Fluctuative lube oil?s demand results in product completion exceed the given due date. This research is conducted to obtain optimal production schedule by using mixed integer linear programming model which is solved by using branch and bound algorithm. By using LINGO 9.0 extended version, researcher obtain optimal production schedule which reduce the total production cost by 29.76%.

Abstrak :
Nowadays, the ready-mixed concrete (RMC) industry plays an important role in construction projects, since it has become one of the mechanisms in construction works and it has become more widely used than in the past. Increasing efficiency is focused on in order to be competitive in business. Therefore, this study aims to increase efficiency of the delivery management system by using the modeling of production planning and management of daily scheduling and dispatching of ready-mixed concrete trucks in order to solve the bottleneck problems of production, which are consequently affecting the RMC delivery process .In fact, the capacity of ready-mixed concrete machines seems to be a limitation, since concrete can only be mixed and then delivered in batches, one vehicle at a time. Earliest Due Date (EDD) and First-Come, First-Served (FCFS) are two techniques of priority rules used for RMC scheduling in providing more precision and accuracy of related inputs which can be used in order improve efficiency of the entire RMC process. In the model, factors affecting the RMC delivery process, such as distances, travel speed and travel times are determined by using GIS–Geographic Information Systems software (ArcGIS). The mapping data is also input into the construction site data, which then builds a model based on priority rules to determine the production and dispatching schedule. Preliminary results from the model indicated that delivery delays can be reduced, in addition to improving daily scheduling and reducing planning time. Moreover, the Single Machine-Multiple Sites model was applied to a concrete truck freight management company that had only one manufacturing machine and it had to deliver to several construction sites in various urban areas. By improving efficiency, by optimizing delivery times and by reducing the cost of waiting time at various sites, this PDRMC model could cut operating costs and increase the company’s revenue because there will be time for more orders.