Judul: Identifikasi titik kritis traceability menggunakan metode pendekatan Failure Modes Effects and Criticality Analysis (FMECA) pada industri pengolahan udang breaded di PT Y
Abstrak: Identifikasi titik kritis traceability digunakan untuk menganalisis dan mengidentifikasi titik kritis pada implementasi internal treacibility dalam proses produksi di perusahaan dengan menggunakan metode Failure Modes, Effect and Criticaly analysis (FMECA). Tujuan dilakukannya penelitian ini adalah menggunakan metode FMECA untuk menganalisis dan mengidentifikasi titik kritis pada implementasi internal treaceability dalam proses produksi udang breaded di PT Y.
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Judul: Evaluasi Sistem Traceability pada Produksi Chewy Candy di PT Sweet Candy Indonesia Menggunakan FMECA (Failure Mode Effects and Criticality Analysis)
Abstrak: The low level of effectiveness and efficiency in traceability system implemented by an industry will conduce bad management of product quality assurance. Therefore, traceability system is necessary to be evaluated using FMECA (Failure Mode Effects and Criticality Analysis) method and arrangement of several mock recalls. Base on FMECA analysis, errors like no documentation of BTP batch number by the flavor room and production; no candy calculation in cut and wrap; damage or disappearance of checklist intermediate form (in transwrap); and no documentation of scrap separately by the incinerator are categorized in unacceptable area which have prefered priority in corrective action compared with errors of candy’s variety and batch number documentation in pulling to cut and wrap; damage or disappearance of non-document pulling form and checklist intermediate form (in copacking) that are categorized in undesirable area. The result of mock recall also show that the total average time consumption at PT Sweet Candy Indonesia is 310 minutes with 168,5 minutes dominated by production. Refer to those result, the effectiveness and efficiency level of traceability system at PT Sweet Candy Indonesia is still low which the maximum limit of 240 minutes as the operational standard is surpassed. In order to elevate the effectiveness and efficiency of traceability system at PT Sweet Candy Indonesia, implementation of kanban system in production can be the best solution in corrective action.
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Judul: The Construction of Greedy SVP LLL Algorithm
Abstrak: A lattice is a set of all integer linear combination of a set of linearly independent vectors in ℝ𝑛���. The independent vectors are called bases of lattice. Any lattice can be generated from many bases, and these bases have the same cardinality. In the lattice, the most fundamental and renowned problem is the Shortest Vector Problem (SVP). SVP is a tracking problem of the shortest nonzero vector in a lattice with equivalent bases. In two dimensions, SVP problem has resolved exactly by Gauss’ algorithm. When the lattice dimension is higher than two, A.K. Lenstra, H.W. Lenstra and L. Lovasz gave a LLL algorithm to compute approximation of nonzero shortest vector in the lattice. Reduced bases solution obtained from LLL algorithm still be an approximation and has polynomial running time of arbitrary dimension which large enough. In 1994, Schnoor and Euchner modified this LLL algorithm as a new variant which later was named deep insertion LLL algorithm. This algorithm is a modified version of the LLL algorithm to the terms of the exchange step to improve the accuracy of output of LLL reduced bases and applying it to the subset sum problem. The purpose of this research are: (1) Reconstruct the LLL algorithm and deep insertion LLL algorithm using a geometric approach. (2) Construct a greedy SVP LLL algorithm. (3) Implement the three algorithms in a symbolic programming language, and evaluate them experimentally. A bases ℬ=[𝐛���1,𝐛���2,…,𝐛���𝑛���] in ℝ𝑚��� is called reduced LLL with parameter 𝛿��� if satisfies: (a) |𝜇���𝑗���𝑖���|≤12, for every integer 𝑖���,𝑗��� with 1≤𝑖���<𝑗���<𝑛���. (b)𝛿���‖𝜋���𝑗���(𝐛���𝑗���)‖2≤‖𝜋���𝑗���(𝐛���𝑗���+1)‖2, for 𝑗���=1,2,…,𝑛���−1,where 𝛿��� is a reduced parameter of real numbers with 14<𝛿���<1. The first requirement is the reduced basis 𝛿��� must “nearly orthogonal” and in its computation case, this requirement can be reached out by using the Gram-Schmidt’s orthogonalization. While the second requirement is called exchange step, or used to called as Lovasz condition. By using both of these requirements, then they establish the LLL algorithm. Then, Schnoor and Euchner modify the LLL algorithm based on the requirements of the exchange step called the deep insertion LLL algorithm, where the exchange step is based on the comparison of the projected vector in orthogonal complement [𝐛���1,𝐛���2,…,𝐛���𝑘���−1]⊥ after j-th reduction. To construct greedy SVP LLL algorithm, the requirements of the exchange step is based on purely by comparing norm of lattice 𝐛���𝑗��� with norm lattice 𝐛���𝑖��� for 𝑖���=1,2,3…,𝑗���−1. The process of insertion reduced vector after the exchange step also has done greedily. Then, we calculate the number of arithmetic operation in greedy SVP LLL algorithm for further analysis. The result of our exprimentation for three algorithms on the certain matrix size shows that the running time of the three algorithms increases propotional to the size of the matrix. The result also shows that by using 𝛿���=34 for the LLL algorithm and the deep insertion LLL algorithm, and the greedy SVP LLL algorithm which is a new variant made by using no parameter of 𝛿���, outperform of the other of two previous algorithm in terms of speed with the same output.
Keyword: LLL algorithm, LLL deep insertion algorithm, greedy SVP LLL algorithm