Masasinar Holdings Sdn. Bhd. is a homegrown automotive parts manufacturer specialising in metal stamping, welding, and assembly of structural components. Over the years, the company has expanded its production capabilities to cater to a wider customer base, including Tier-1 vendors and OEMs, while maintaining a strong commitment to supporting Malaysia’s local content development agenda. Its operations focus on delivering high-quality, durable components with competitive lead times. During the Gemba visit, the assessment team conducted a comprehensive walkthrough of key production areas, from raw material processing to final product inspection. Observations centred on production efficiency, quality control procedures, and equipment maintenance practices. Discussions with management revealed an interest in adopting AI solutions to improve operational visibility, enhance defect detection accuracy, and optimise resource utilisation. Potential AI applications identified include predictive maintenance to minimise downtime, real-time production monitoring for improved scheduling, and data analytics for root cause identification in quality issues. The visit confirmed Masasinar Holdings’ readiness to integrate AI-driven productivity tools, supported by its existing operational data and commitment to continuous improvement under the AutoPN framework.

MEPN conducted an online briefing with First Win Marketing Sdn. Bhd. as part of the ongoing Project Pintar initiatives. The session served to introduce the objectives and framework of Project Pintar, while engaging the company in discussions on potential productivity improvement strategies tailored to their operations. This engagement reflects MEPN’s commitment to fostering collaboration with industry players in driving productivity growth and operational excellence within the machinery and equipment (M&E) ecosystem

PACU secara prinsipnya menyokong penuh pelaksanaan projek tersebut dan menekankan kepentingan bagi semua data dan dapatan daripada pelaksanaan ini untuk direkod serta dilaporkan dengan sistematik. Laporan-laporan ini dilihat penting untuk digunakan sebagai rujukan bagi pembentangan kepada pihak berkepentingan di peringkat tertinggi. PACU juga telah menekankan keperluan untuk mengenal pasti dan mengukur impak projek secara berstruktur. Antara indikator utama yang dicadangkan termasuk pengurangan masa pemprosesan permohonan perniagaan, penjimatan kos pematuhan serta tahap kepuasan pengguna akhir. Penilaian impak ini dijangka akan membantu dalam memperoleh sokongan dasar serta peluasan pelaksanaan di peringkat negeri yang lebih luas pada masa akan datang. #SarawakProduktif #MemacuProduktivitiNegara #EODB

The program featured opening remarks by Dr. Mazlina Shafi’i, Director of MPC Sarawak, and Ts. Zakri Md. Salleh, Chief Technology Officer of Sarawak Skills. Participants were guided to develop a Proof of Concept (POC) project for potential implementation in their respective organizations. This initiative marks a significant step in driving digital transformation and productivity enhancement among Sarawak’s industries, reinforcing AI as a key enabler in future-proofing business operations. #SarawakProductive #AIforProductivityTransformationProgram

Ia bertujuan memastikan kelancaran pelaksanaan projek dengan memberi penekanan kepada simulasi aliran proses baharu di lapangan. Melalui pendekatan ini, pegawai pihak berkuasa tempatan (PBT) diberi peluang untuk meningkatkan kompetensi mereka, khususnya dalam penggunaan sistem eR & DO dan pemahaman menyeluruh terhadap peranan mereka di kaunter semakan. Selain itu, uji kaji ini turut dilaksanakan secara langsung di UTC Sibu (melibatkan Majlis Perbandaran Sibu dan Majlis Daerah Luar Bandar Sibu) dan di Majlis Daerah Kanowit. Pelaksanaan di kedua-dua lokasi telah menghasilkan keputusan yang positif, antaranya pendaftaran 10 permohonan baharu bagi Pendaftaran Nama Perniagaan (BNR), 5 permohonan baharu bagi Lesen Perdagangan (TL), dan 1 permohonan baharu bagi Lesen Operasi pada 1 Ogos 2 . Hasil pemerhatian awal pada hari pertama menunjukkan terdapat beberapa aspek yang perlu ditambah baik bagi meningkatkan keberkesanan keseluruhan proses. Antara yang dikenal pasti termasuk keperluan menambah baik proses semakan dokumen agar lebih efisien, penambahbaikan borang superform, peningkatan kompetensi pegawai di kaunter semakan, serta memperkukuh komunikasi berhubung aliran proses. Penambahbaikan ini dijangka memberi impak positif kepada kelancaran urusan perniagaan dan meningkatkan keyakinan usahawan tempatan dalam memulakan perniagaan mereka. #SarawakProduktif #MemacuProduktivitiNegara

Sesi produktif ini bertujuan meneroka peluang kerjasama strategik melalui pelaksanaan Inisiatif Integrasi Data, khususnya dalam konteks pengangkutan bahan kimia bersama LTH Trading & Transport Sdn. Bhd. dengan perkongsian cabaran-cabaran yang dihadapi seperti keperluan pematuhan pelbagai peraturan, pengesanan masa nyata (real-time tracking), dan isu-isu penyelarasan dokumentasi serta pengurusan pemandu. Perbincangan turut meneliti kemungkinan pelaksanaan sistem integrasi data dengan pihak LTH sebagai syarikat rintis. Pelaksanaan ini dijangka dapat meningkatkan pemantauan perjalanan, mempercepatkan aliran maklumat antara syarikat dan agensi pengawal selia, serta mewujudkan satu sistem pelaporan yang lebih cekap yang akan memberi impak positif terhadap produktiviti dan meningkatkan pematuhan dalam kalangan pengendali logistik bahan kimia.

Fuji Seats (Malaysia) Sdn. Bhd. is a Tier-1 automotive component manufacturer specialising in the production of complete seat systems for major automotive OEMs. With fully integrated operations—including stamping, welding, foaming, and final seat assembly—the company upholds stringent standards for safety, ergonomics, and product consistency. As part of its continuous improvement agenda, Fuji Seats is actively seeking innovative solutions to drive efficiency and enhance customer satisfaction. During the Gemba visit, the AutoPN team conducted a detailed walkthrough of the plant’s production flow, covering sub-component manufacturing to final seat module assembly and testing. Key focus areas included traceability systems, real-time production visibility, and quality control checkpoints. The company expressed strong interest in leveraging AI to automate defect classification, monitor operator performance, and optimise comfort testing processes. Opportunities identified include the application of AI in predictive maintenance, vision-based quality inspection, and data analytics for performance optimisation. With a wealth of operational data already available from production equipment and testing systems, Fuji Seats is well-positioned to pilot AI solutions that support its goals for productivity gains and product excellence under the AutoPN initiative.