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.

Efficiency Gains and Reductions in Furnace Maintenance Through the Use of High Temperature Ceramic Coating Technology

Unique high temperature, energy efficient ceramic coatings are being used in heat treating and forging furnaces around the globe to reduce the high cost of refractory maintenance, reduce fuel consumption and improve furnace efficiencies as well as product quality. In addition, these coatings also protect metal from oxidation when used at elevated temperatures as well as corrosion in caustic environments. We will show how these specialized ceramic coatings can provide energy savings depending on the fuel being used, the furnace operation, furnace configuration, and production schedule of at least up to 20%. Additionally, we will show that furnace heat up and turn-around times are decreased and how the service life of ceramically coated refractories are extended.

Production Scheduling Mathematical Model in Garment Industry

In this paper, the author introduces about building the support system of production schedule, based on the linear programming model, exploiting effectively Branch and Bound (BnB) algorithms in Lingo software. In addition, the result of the study is the software that supports production schedule based on the C# programming language, friendly interface makes the operator easy to use. After the implementation and final test, the research model is applied to the case of the garment company to support the production schedule, reduces the number of orders delayed, shorten the production time to increase profits for the company.

Production Scheduling Mathematical Model in Garment Industry

In this paper, the author introduces about building the support system of production schedule, based on the linear programming model, exploiting effectively Branch and Bound (BnB) algorithms in Lingo software. In addition, the result of the study is the software that supports production schedule based on the C# programming language, friendly interface makes the operator easy to use. After the implementation and final test, the research model is applied to the case of the garment company to support the production schedule, reduces the number of orders delayed, shorten the production time to increase profits for the company.

ANALISIS PENGENDALIAN MUTU DALAM MENINGKATKAN PROSES PRODUKSI

This research is motivated by the still not optimal quality control in the production of Nata De Coco which can be seen from the decrease in customer satisfaction, namely the reduced demand for products from consumers, this is thought to be caused by the not optimal implementation of quality control carried out by the company. The research method used in this study is a qualitative descriptive research method. Based on the results of the study that: 1) The implementation of quality control at the Nata De Coco Factory Bojongmengger Ciamis has been carried out quite well in accordance with the indicators that have been set in this study, namely performance, features, reliability, conformance, durability, service ability, aesthetics and quality which shows that it is quite good; 2) The production process at the Nata De Coco Factory Bojongmengger Ciamis is generally good because it is in accordance with the indicators that have been set in this study, which include the production schedule, production sequence and production time which show that it is good; 3) The implementation of quality control plays a role in improving the production process at the Nata De Coco Factory Bojongmengger Ciamis. It can be seen that with the implementation of quality control which is already quite good, it has an impact on increasing the production process at the Nata De Coco Factory in Bojongmengger Ciamis. Thus, if the implementation of quality control is good, the company's production process will increase.

Sequence learning-based schedule prediction for flexible manufacturing systems under uncertainties

This study presents a method of production schedule prediction for flexible manufacturing systems with consideration of the uncertainty factors including limited machine capacity, diverse processing time and unplanned waiting time. The proposed method can predict product-level schedules using sequence learning, which derives data-learned models to predict production sequence proactively and granularly at the product-level. A decision tree technique is applied to derive such predictive models to pre-trace the locations of individual products allocated to each workstation. A deterministic technique is also applied to estimate waiting and production time per product as well as total production time consumed to fabricate all products assigned by work orders.

Hanna-Barbera’s Cacophony: Sound Effects and the Production of Movement

Zaps, crashes, boinks, and bangs flooded TV’s airwaves with the rise of Hanna-Barbera Productions at the end of the 1950s, and these sound effects have been heard ever since. Hanna-Barbera Productions created and proliferated one of the most recognizable collections of sounds in television and animation history. This article traces the formation of Hanna-Barbera’s library of sound effects and how these sound effects operate within the studio’s cartoons. Motored by television’s demanding production schedule and restrictive budgets, Hanna-Barbera persistently recycled its sound effects across episodes, seasons, and series. These sound effects, heard over and over again, were paired to the studio’s brand of limited animation – a form of animation that is often seen as kinetically wanting – to enliven images through sonically invoking movement, what this article calls trajectory mimesis. This logic of trajectory mimesis facilitates the repetition of the studio’s sound effects. These conditions – television’s economic restraints and the studio’s limited animation aesthetics –provided the ideal conditions for the creation of Hanna-Barbera’s iconic library of sound effects.

Perencanaan Produksi dan Pengendalian Persediaan pada Perusahaan Manufaktur

ABSTRACT This research was conducted with the aim of observing the production planning process applied by PT X then designing a comprehensive production planning and inventory control so that it can overcome the occurrence of shortages and excess of inventory in the company. The research was conducted by observing a springbed manufacturing company PT X in Makassar. The data used are primary and secondary data, using instruments such as interviews, conducted on staffs and management of PT X, site visits, as well as company historical data. The results of the research were in the form of production planning, through demand forecasting, master production schedule, and planning for resource requirements. In addition, the researcher also established an inventory control system that could support the company's production process using the EOQ method, safety stock, and reorder points. The results of the research are not necessarily applicable to other companies with different demand patterns or to companies with different industries. In addition, the methods used in production planning and inventory control are limited in this study. ABSTRAK Penelitian ini dilakukan dengan tujuan untuk mengamati proses perencanaan produksi yang diterapkan perusahaan manufaktur PT X, merancang perencanaan produksi dan pengendalian persediaan yang komprehensif sehingga dapat mengatasi terjadinya kekurangan maupun kelebihan persediaan pada perusahaan. Penelitian dilakukan dengan melakukan observasi pada perusahaan manufaktur PT X, perusahaan manufaktur yang memproduksi kasur per di kota Makassar. Data yang digunakan merupakan data primer dan sekunder, berupa wawancara yang dilakukan pada jajaran staf dan manajemen PT X, serta data historis perusahaan. Hasil penelitian berupa perencanaan produksi yang melewati tahap peramalan permintaan, pembentukan jadwal induk produksi, serta perencanaan kebutuhan sumber daya. Selain itu, peneliti juga membentuk sistem pengendalian persediaan yang dapat mendukung kelancaran proses produksi perusahaan dengan metode Economic Order Quantity (EOQ), persediaan pengaman, dan titik pemesanan kembali. Hasil penelitian belum tentu dapat diterapkan pada perusahaan lain dengan pola permintaan maupun pada perusahaan dengan industri yang berbeda. Selain itu, metode yang digunakan dalam pembentukan perencanaan produksi dan pengendalian persediaan pun menjadi keterbatasan dalam penelitian ini.

The Use of Mathematical Programming to Determine Optimal Production and Drilling Schedule in an Offshore Oil Field, A Case Study From the Barents Sea

A field with two neighboring reservoirs was discovered in the Barents Sea in 2013 and 2014. After a successful extended well test of an appraisal well in 2018 and initial field planning tasks, a preliminary drilling and production schedule was proposed based on cross-domain collaboration and group work involving several disciplines. In this paper, mathematical programming is employed to model and optimize the economic value of the project in order to determine the best drilling and production schedule for the field. The optimization includes some of the technical constraints considered by the field development team while also considering uncertainties such as reservoir size, productivity of well, and cost. These have been systematically evaluated by using simulation-based optimization (sampling). The results were that the use of mathematical programming allows the field planner to evaluate several scenarios within a reasonable time frame, thereby enabling rapid changes in the decisions to respond to new information and risk considerations in a dynamic environment. This paper illustrates the benefits of utilizing mathematical programming in early field planning to optimize the drilling and production schedule.