Smart Master Production Schedule for the Supply Chain: A Conceptual Framework

Risks arising from the effect of disruptions and unsustainable practices constantly push the supply chain to uncompetitive positions. A smart production planning and control process must successfully address both risks by reducing them, thereby strengthening supply chain (SC) resilience and its ability to survive in the long term. On the one hand, the antidisruptive potential and the inherent sustainability implications of the zero-defect manufacturing (ZDM) management model should be highlighted. On the other hand, the digitization and virtualization of processes by Industry 4.0 (I4.0) digital technologies, namely digital twin (DT) technology, enable new simulation and optimization methods, especially in combination with machine learning (ML) procedures. This paper reviews the state of the art and proposes a ZDM strategy-based conceptual framework that models, optimizes and simulates the master production schedule (MPS) problem to maximize service levels in SCs. This conceptual framework will serve as a starting point for developing new MPS optimization models and algorithms in supply chain 4.0 (SC4.0) environments.

RAW MATERIAL INVENTORY PLANNING OF PATIENT MENU USING MATERIAL REQUIREMENT PLANNING (MRP) IN RSIA KENDANGSARI MERR SURABAYA

Introduction: Material Requirement Planning (MRP) is a technique or a logical procedure to translate the Master Production Schedule (MPS) of the finished goods or end item into the net requirements for some of the components needed to implement the MPS. MRP is used to determine the amount of material needs to support the Master Production Schedule and when the material needs to be scheduled.Methods: The study is conducted on 13 August 2018 until 12 September 2018 at the installation Nutrition RSIA Kendangsari Merr Surabaya. Collecting data in this study using several methods, including: observation- This stage is conducted in all parts related to the object of study, starting from the Purchase Order (PO) by a head cook up to raw material stored in the storage, discussion- author interviews and collects data to communicate and discuss with the respondents. Respondents in this study are the head of the nutrition unit and head cook of RSIA who have the authority doing the purchasing.Results: Planning of procurement of raw materials to the menu rawon in RSIA can use the Exponential Smoothing method. The discussion has compared two methods of forecasting and the results are consistent with the demand’s patterns of Simple Moving Average method, Exponential Smothing. Forecasting has the lowest error rate by using Exponential Smoothing. The second conclusion is a technique of determining the appropriate Material Requirement Planning in raw material procurement to menu rawon in RSIA is using Lot for Lot.

Developing a Master Production Schedule Using Fuzzy Mixed Integer Linear Programming

This paper considers the hierarchical production planning (HPP) concept to solve a production planning problem in the process industry in a fuzzy environment. The adopted fuzzy HPP consists of two levels in which a fuzzy aggregate production planning (FAPP) model is developed in the first level, and then a fuzzy disaggregate production planning (FDPP) model is developed at the second level. The FAPP was reported by Omar et al. [1] and therefore, this research paper discusses the FDPP model. We formulated the disaggregate model as a fuzzy mixed-integer linear programming model that aims to develop a master production schedule in which numbers of optimal batches are developed in presence of setup time. In addition, we evaluate the performance of the FMILP by comparing its results with a previously reported approach. The findings indicate that significant cost savings were achieved by adopting the fuzzy mathematical programming approach.

PRODUCTION PLANNING RAMBAK CRACKER TO MEET DEMAND AT UMKM DWI JAYA KENDAL

UMKM Dwi jaya merupakan suatu perusahaan kerupuk rambak yang terletak di Jl. Kyai Guru Sulaiman, Pegandon, Kabupaten Kendal, Jawa Tengah 51357. UMKM Dwi Jaya membuat dua produk yaitu kerupuk rambak sapi dan kerupuk rambak kerbau. Di UMKM Dwi jaya sendiri menggunakan sistem make to stock yaitu membuat suatu produk akhir untuk disimpan dan kebutuhan konsumen akan diambil dari persediaan di gudang. Tingkat persediaan tergantung pada waktu respon permintaan pelanggan dan tingkat vabilitas permintaan.Perusahaan tersebut memiliki sebuah masalah yaitu jumlah permintaan yang dihasilkan lebih banyak dari jumlah produksi yang ada sehingga menyebabkan kerupuk rambak tersebut mengalami kekurangan, Tindakan yang dapat dilakukan untuk mengatasi permasalahan tersebut yaitu membuat rencana produksi agar dapat memenuhi permintaan tepat waktu, tepat jumlah dengan biaya minimum yaitu dengan melakukan peramalan produksi dengan menggunakan Exponential smoothing kemudian dilanjutkan dengan menggunakan perencaaan agregat dengan menggunakan metode heuristik dan penjadwalan produksi menggunakan Master Production Schedule (MPS) sesuai dengan metode heuristik yang terpilih, Setelah itu MPS akan diverifikasi dengan menggunakan menggunakan Rough Cut Capacity Planning (RCCP) agar bisa mengetahui layak tidaknya jadwal dari MPS tersebut. Lalu dilakukan rekomendasi perbaikan untuk mengurangi biaya produksi, biaya simpan dan biaya tenaga kerja dengan menggunakan metode-metode yang tepat.Dari hasil penelitian, forecasting dengan menggunakan metode Exponential smoothing dan metode moving average menghasilkan peramalan terbaik total permintaan untuk kerupuk rambak sapi sebesar 88625 gram dan untuk kerupuk rambak kerbau sebesar 89390,52 gram, pada Aggregate Planning dengan menggunakan metode heuristik didapatkan hasil dengan solusi terbaik adalah solusi pengendalian persediaan (level strategy) total biaya terendah sebesar Rp. 0. (MPS) sesuai dengan solusi terbaik pada Aggregate Planning dan sesuai dengan kapasitas mesin dan pekerja yang telah di verifikasi menggunakan Rough Cut Capacity Planning (RCCP)

Multi-Objective Master Production Schedule for Balanced Production of Manufacturers

Focusing on the balanced use of production capacity in the formulation of master production schedule (MPS), this paper sets up a single-product, multi-stage, multi-objective MPS model based on balanced production. Whereas the model aims to achieve multiple objectives through nonlinear integer programming, a genetic algorithm based on automatic transformation (AT-GA) was designed to solve the model. Specifically, the chromosomes were encoded as integers to satisfy the model constraints; the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was adopted to handle the four nonlinear objectives of the model, thereby obtaining the fitness function; the fuzzy logic control (FLC) was introduced to automatically adjust the crossover and mutation parameters, and balance the global and local search abilities of the GA, enhancing the computing power of the algorithm. The experimental results show that the AT-GA can effectively solve the multi-objective MPS optimization problem under balanced production.

ANALISIS PERENCANAAN BAHAN BAKU DI UD. AA DENGAN MENERAPKAN METODE MATERIAL REQUIREMENT PLANNING (MRP)

This study discusses the application of the material requirements planning (MRP) method in the planning of raw materials in a furniture company. The purpose of this research is to know the planning of raw materials for furniture products in UD. AA, determine the most suitable inventory model to be applied to material inventory planning and analyze the role of the MRP system in raw material procurement planning. The forecasting method used is the quantitative method of time series analysis, determining the master production schedule, calculating lot sizing (LFL, EOQ, POQ methods). From determining the Master Production Schedule, it is found that the cabinet production plan for the next three months is 4 units per period or week, and based on the calculation of Material Requirement Planning (MRP) it can be seen what components are needed for the manufacture of cabinets, how many and when each component is required. Therefore it is obtained that the total raw material requirement for wood for the next three months is 11.34 m³.

Solving multi-objective master production schedule problem using memetic algorithm

<span>A master production schedule (MPS) need find a good, perhaps optimal, plan for maximize service levels while minimizing inventory and resource usage. However, these are conflicting objectives and a tradeoff to reach acceptable values must be made. Therefore, several techniques have been proposed to perform optimization on production planning problems based on, for instance, linear and non-linear programming, dynamic-lot sizing and meta-heuristics. In particular, several meta- heuristics have been successfully used to solve MPS problems such as genetic algorithms (GA) and simulated annealing (SA). This paper proposes a memetic algorithm to solve multi-objective master production schedule (MOMPS). The proposed memetic algorithm combines the evolutionary operations of MA (such as mutation and Crossover) with local search operators (swap operator and inverse movement operator) to improve the solutions of MA and increase the diversity of the population). This algorithm has proved its efficiency in solving MOMPS problems compared with the genetic algorithm and simulated annealing. The results clearly showed the ability of the algorithm to evaluate properly how much, when and where extra capacities (overtime) are permitted so that the inventory can be lowered without influencing the level of service. </span>

Aplikasi Material Requirement Planning Mempertimbangkan Waktu Pemesanan Bahan Baku

Dalam perusahaan manufaktur kebutuhan persediaan bahan baku dan penjadwalan peroduksi sangat diutamakan. Pemesanan oleh konsumen menjadi tolak ukur perusahaan dalam menentukan kebutuhan produksi. Selama ini perusahaan belum merencanakan kebutuhan bahan yang akan digunakan yang membuat terkadang terjadi penumpukan bahan dan tidak tersedianya bahan di gudang yang membuat proses produksi terhambat. Dengan tidak tersedianya bahan di gudang membuat perusahaan perlu melakukan pembelian bahan untuk mendukung proses produksi, masih banyak perusahaan manufaktur yang belum mempertimbangkan lamanya waktu tunggu (leadtime) untuk bahan sampai ke gudang yang membuat proses produksi terhambat dan tidak dapat memprediksi kapan produksi mulai karena belum tersedianya bahan. Untuk mengatasi masalah tersebut, maka dibuat aplikasi berbasis web yang dapat menangani perencanaan pengadaan persediaan bahan, penjadwalan produksi yang mempertimbangkan waktu pemesanan bahan baku menggunakan metode Material Requirement Planning (MRP).Proses pengembangan menggunakan metode prototype (prototyping model).Aplikasi yang dibangun mampu menghasilkan tabel Master Production Schedule (MPS), tabel Material Requirement Planning (MRP), serta menghasilkan laporan pemesanan dan laporan pembelian. Pembangunan aplikasi menggunakan bahasa pemprograman Framework Codeigniter dengan bahasa skrip Hypertext Preprocessor (PHP).