The global competition encourages Indonesia to advance the economy, especially in manufacturing by implementing sustainable manufacturing. Companies must consider transportation costs and concern for the environment due to the large increase in greenhouse gas emissions and the increase in NOx, Particulate, and various other harmful pollutants. Emissions from transportation activities cause global climate change and damage air quality and human health in regional and urban areas. At the same time, the movement of empty containers can result in air pollution due to CO2 emissions which have a negative impact on sustainable development. This study aims to reduce carbon emissions in the logistics transportation chain in the Automotive Manufacturing Industry. The method used is the Eight Step Approach. The method used is systematic and structured from defining the problem to standardizing improvements. Analysis of the causes of the problem and proposed improvements are determined by Focus Group Discussion (FGD) with expert judgment. The source of the data obtained comes from field observations, FGD, company reports from 2019 to 2021. This research has proven that reducing carbon emissions has an impact on company profits. The largest decrease was contributed by improvements in transportation routes. The ratio of reducing carbon emissions by 2020 is 2.6% or an increase in efficiency compared to the previous year.

PT. Selamat Sempurna  Other   (SSO)  adalah  perusahaan  yang  bergerak  pada bidang komponen otomotif khususnya dalam pembuatan Fuel Tank mobil khusus untuk mobil besar. Dalam upaya mempertahankan kualitas produk, PT. SSO berusaha untuk meminimalisasi jumlah kecacatan dalam setiap unit inspeksinya. Untuk itu diperlukan sebuah metode pengendalian dan peningkatan kualitas untuk mengidentifikasi cacat ke penyebab akar utamanya. Dari pengumpulan data yang dilakukan di PT. SSO dari bulan Januari sampai dengan Desember 2014, didapatkan bahwa cacat bintik debu (dirt) merupakan jenis cacat terbesar yang terjadi di PT.SSO yaitu sebesar 20,92% dan hal ini terjadi pada proses pengecatan Lalu pada tahap berikutnya setelah dilakukan proses brainstorming dengan pihak terkait di dalam perusahaan untuk mencari penyebab utama cacat bintik debu yang kemudian hasilnya ditampilkan melalui diagram fishbone. Untuk mengetahui prioritas perbaikan atau tindak lanjut terhadap penyebab-penyebab yang dipaparkan dalam diagram fishbone maka digunakanlah metode Six Sigma. Dari hasil pengolahan dengan metode Six Sigma didapatkan penyebab utama yang paling  signifikan  dalam  terhadap  cacat  bintik  adalah  faktor  Temperature  dan Speed  Conveyor  dan  faktor  lingkungan.  Pada  tahap  selanjutnya,  dilakukan analisis perbaikan dengan menggunakan model DMAIC, setelah itu melalui hasil Analyze yang didapatkan, modus kegagalan potensial yang paling utama sebagai penyebab terjadinya kecacatan harus segera ditangani. Dalam hal ini modus kegagalan potensial terbesar yang menyebabkan cacat bintik debu (dirt), dengan nilai Level Sigma adalah, adalah parameter seting. Maka tindakan yang perlu dilakukan adalah membuat standar untuk parameter seting temperature dan speed conveyor dan frekuensi pembersihan secara teratur terutama di ruang aplikasi pengecatan.

Tenaga listrik sudah menjadikebutuhan utama bagi masyarakat Indonesia, tetapi tidak dapat dihasilkan secara instan melainkan melalui suatu proses produksi pembangkitan energi listrik di pembangkit listrik. PT PJB Unit Pembangkitan Muara Tawar merupakan salah satu unit pembangkit di Kabupaten Bekasi dengan daya terpasang 2,062 MW, produksi listrik disalurkan melalui SUTET 500 KV ke Gardu Induk Cibatu dan Cawang.  Permasalahannya adalah sering terjadi gangguan yang mengakibatkan kerugian produksi dan ketidakandalan sistem jaringan. Tujuan penelitian ini melakukan evaluasi pembangkit gas turbin dengan menggunakan Generating Availability Data System (GADS), analisis probabilitas dan reliability menggunakan distribusi weibull.  Aplikasi Failure Modes Efect Analisys dilakukan untuk mendapatkan nilai Risk Prioritas Number (RPN) prioritas dan strategi pemeliharaan guna melakukan perbaikan kinerja. Hasil analisa kesiapan unit pembangkit diperoleh hasil antara 88,16 - 88,24 persen, nilai capacity factor (CF) antara 58,44 - 65,59 persen. Jumlah kegagalan gas turbin GT11 sebanyak 19 kali dan menghasilkan parameter beta sebesar 0,6096 dan eta sebesar 1133,6664; gas turbin GT 12 kegagalan sebanyak 15 kali menghasilkan parameter mean sebesar 5,6919 dan standar deviasi  sebesar 2,6612; sementara kegagalan gas turbin GT 13 dengan parameter lamda sebesar 0,0003 dengan jumlah kegagalan 10 kali.  Hasil analisis Pareto ditemukan lima peralatan kritikal, selanjutnya dilakukan Failure Mode Efect Analisys untuk rekomendasi pemeliharaan.

In the case of delivery of goods for export purposes with large box dimension variations, the arrangement of goods in the fleet becomes very important as it affects the efficiencies of the cost. This situation is felt by all industrial sectors, one of which is the automotive industry. One problem is due to loading container issues, which in this case is due to the use of fleets for unfilled shipping. This is due to the fact that the delivery pattern of goods within the shipping ship is still not optimal. One solution is to optimize the space and layout of the items in the fleet. Genetic algorithm is a method of solving solutions that can be used to solve container loading problems with non-linear and heterogeneous data items, inspired by the theory of evolution. Genetic algorithm can provide optimization solutions for item preparation patterns that practice natural selection methods to get selected individuals that contain the best genes. Then the data will be repeated for several generations and yield the best array pattern output or achieve the target, in this case the minimum free space.

Every village has Village Superior Products (Prudes) which have economic value that can advance the economy of rural communities. However, the consolidation of the Prudes results is still not optimal, it can be seen from the poverty rate in rural areas which is still high when compared to the level of poverty in the city. To overcome this, it requires the efficiency and effectiveness of distribution centers in rural supply chain systems in order to consolidate the Prudes products from a number of villages to a number of customers/consumers. However, the main problem is how many distribution centers are needed and where are the distribution centers located in an area that has the same type of Prudes. Therefore, the aim of this research is to find the best location P from a number of candidates distribution centers (N = 59 villages) where P ≤ N. To achieve the objectives of this study, the P-Median method is used with the help of AMPL software as a data processing tool. in order to complete the model of the P-Median. The objective function of the P-Median model is to find the minimum value of the total cost based on distance (), production volume (), shipping costs (), and fixed cost () at a number of DC facilities. In the process before the completion of the P-Median model, the approach is first carried out proximity analysis which consists of the pre-qualification and qualification processes in determining candidate facility candidates distribution center. This approach was taken to cover the limitations of APML software in processing data. The result of this research is that the optimal number of DC facilities in five DC facilities with a total cost minimum of IDR 91.80 billion. Meanwhile, the facilities are distribution center located in the village of Sanuanggamo, North Tongauna District (P11), Awuliti Village, Lambuya District (P17), Mumundowu Village, Pondidaha District (P36), Duriasi Village, Wonggeduku District (P44), and Puday Village, West Wonggeduku District (P53).