{"id":4854,"date":"2025-11-14T10:00:28","date_gmt":"2025-11-14T01:00:28","guid":{"rendered":"https:\/\/ohtavn.com\/?post_type=media&p=4854"},"modified":"2025-11-25T18:41:27","modified_gmt":"2025-11-25T09:41:27","slug":"logistics-efficiency-in-manufacturing","status":"publish","type":"media","link":"https:\/\/ohtavn.com\/en\/media\/logistics-efficiency-in-manufacturing\/","title":{"rendered":"Logistics efficiency in manufacturing: Optimizing supply chain in screw procurement"},"content":{"rendered":"
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Introduction<\/h3>\n

To keep production lines running, it is essential to procure every component, even a screw weighing just a few grams, reliably and at the right time. However, on the actual factory floor, numerous challenges arise daily, including setting order lots for screw procurement, managing transport lead times, and securing inventory space. This article provides a practical approach to achieving lead time reduction, logistics efficiency<\/strong>, and cost reduction<\/strong> by taking a comprehensive look at the entire supply chain, starting with screw procurement<\/strong>.<\/p>\n

First, for our target audience\u2014purchasing, production control, and management personnel in high-mix, low-volume manufacturing\u2014we will re-examine the impact of screw procurement on the supply chain and clarify how its efficiency directly contributes to company-wide profits. Next, we will introduce strategic methods such as inventory optimization based on demand forecasting, and supplier consolidation\/multi-sourcing, linking them with the latest trends in Asian manufacturing hubs, including Vietnam.<\/p>\n

Furthermore, we will explain specific measures step-by-step, such as real-time visualization through the implementation of WMS (Warehouse Management System) and TMS (Transport Management System), automation of screw standard management like ISO\/JIS, and optimization of warehousing and transportation with an eye toward decarbonized logistics. By the end of this article, you will have a checklist and a roadmap that you can immediately apply to your company’s supply chain.<\/p>\n

This article explains the key points of supply chain optimization, starting from the perspective of screw procurement.<\/p>\n

The Impact of Screw Procurement on Logistics Costs<\/h3>\n

Fastening components such as screws and bolts account for a low percentage of the total product cost, around 1-3%<\/strong>. However, they are “high-risk, low-cost” elements that can dramatically increase total costs if they trigger a line stoppage or quality defects. This is where the perspective of TCO (Total Cost of Ownership)<\/strong> becomes crucial. By quantifying not only the unit price but also storage fees from order lots, transportation costs, inspection and sorting labor, re-procurement costs for non-conforming parts, and even opportunity loss from line downtime, we can visualize the impact of screw procurement on overall logistics costs.<\/p>\n

TCO = Purchase Price + Transportation Cost + Inventory Holding Cost + Quality Risk Cost + Line Stoppage Loss<\/strong><\/p><\/blockquote>\n

For example, if you bulk-purchase a three-month supply of screws used at a rate of 5,000 pieces per month at a unit price of 5 yen, the order amount is 75,000 yen. However, when you add inventory holding costs (warehouse space efficiency, interest equivalent), stocktaking work, and labor costs, it is not uncommon for the actual cost to be about 1.3 times<\/strong> higher. Identifying these hidden costs is the first step in procurement strategy.<\/p>\n

Measuring Logistics Efficiency with KPIs<\/h4>\n

The following three indicators are effective for quantitatively evaluating progress in logistics efficiency.<\/p>\n\n\n\n\n\n\n
Indicator<\/strong><\/td>\nDefinition<\/strong><\/td>\nTarget Guideline<\/strong><\/td>\n<\/tr>\n
Inventory Turnover Rate<\/td>\nAnnual Sales Revenue \u00f7 Average Inventory Value<\/td>\n12 times\/year or more (less than 1 month of inventory)<\/td>\n<\/tr>\n
Lead Time<\/td>\nTotal days from order to receiving<\/td>\nFor Japan: within 14 days; Within Vietnam: within 5 days<\/td>\n<\/tr>\n
OTD (On-Time Delivery)<\/td>\nPercentage of deliveries made on the scheduled date<\/td>\n98% or higher<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
    \n
  • A low Inventory Turnover Rate<\/strong> often indicates issues with excessive safety stock settings or large lot sizes.<\/li>\n
  • To shorten Lead Time<\/strong>, contracts for EDI (Electronic Data Interchange) or VMI (Vendor-Managed Inventory) with suppliers are effective.<\/li>\n
  • OTD<\/strong> serves as a “health check” indicator, reflecting not only logistics but also the supplier’s production planning and quality control levels.<\/li>\n<\/ul>\n

    By constantly monitoring these KPIs on a dashboard and rapidly running the PDCA cycle to identify bottlenecks, supply chain optimization<\/strong> originating from screw procurement will become established at the operational level.<\/p>\n

    Shortening Lead Times with Demand Forecasting and Inventory Optimization<\/h3>\n

    Even in the Vietnamese market, which is said to have fewer seasonal fluctuations than Japan, the demand for screws fluctuates significantly in cycles<\/strong>, such as the surge in demand before and after the Lunar New Year (Tet) and during the equipment inspection periods of foreign-affiliated suppliers. The key to minimizing inventory while absorbing these fluctuations is the combination of data-driven demand forecasting and inventory optimization.<\/p>\n

    Prioritizing with ABC Analysis<\/h4>\n
      \n
    1. A-Rank (High in both importance and consumption)<\/strong>: High risk of stockouts, so demand is forecasted daily and automatically replenished promptly using a reorder point system.<\/li>\n
    2. B-Rank (Medium)<\/strong>: Use a combination of weekly forecasting and periodic ordering to maintain inventory turnover.<\/li>\n
    3. C-Rank (Infrequent)<\/strong>: Although the unit price is low, the procurement cost is relatively high, so lot ordering + supplier inventory (VMI) is used to outsource the storage location.<\/li>\n<\/ol>\n

      Visualizing the ABC ranks allows you to concentrate resources on the most impactful A-rank items.<\/p>\n

      Dynamic Safety Stock Setting<\/h4>\n

      In Vietnam, it is not uncommon for lead times to be delayed by +2 to 3 days<\/strong> from the schedule due to port congestion and road infrastructure issues. Therefore, adopting a dynamic safety stock model<\/strong> using the coefficient of variation (CV) allows for the automatic increase or decrease of buffers during periods of high demand volatility.<\/p>\n

      Safety Stock = Z-score \u00d7 \u221a(Demand Variation\u00b2 \u00d7 Lead Time + Supply Variation\u00b2)<\/strong><\/p>\n

        \n
      • Z-score: Stockout tolerance rate (e.g., 1.65 for a 95% service level)<\/li>\n<\/ul>\n<\/blockquote>\n

        By collecting actual screw usage data online with IoT sensors and recalculating demand variation daily, you can suppress both “overstocking” and “shortages.”<\/p>\n

        Optimization Without Warehouse Expansion through VMI (Vendor-Managed Inventory)<\/h4>\n

        For items with unpredictable demand fluctuations, a VMI scheme<\/strong>, where the supplier manages the inventory, is powerful. At GIS OHTA VIETNAM, we have established micro-depots in Ho Chi Minh City in collaboration with major screw suppliers, realizing operations such as:<\/p>\n

          \n
        • Order by 3 PM today \u2192 Arrives at the factory by 8 AM tomorrow<\/strong><\/li>\n
        • Inventory data is shared in real-time via EDI<\/li>\n<\/ul>\n

          This has resulted in significant improvements in both lead time and cost:<\/p>\n\n\n\n\n\n\n
          <\/td>\nBefore Implementation<\/strong><\/td>\nAfter Implementation<\/strong><\/td>\n<\/tr>\n
          Safety Stock Days<\/td>\n10 days<\/td>\n4 days<\/strong> (\u25b260%)<\/td>\n<\/tr>\n
          Emergency Air Freight Costs<\/td>\n1.2 million JPY\/month<\/td>\n150,000 JPY\/month<\/strong> (\u25b287%)<\/td>\n<\/tr>\n
          Stockout Incidents<\/td>\n8 cases\/month<\/td>\n0 cases<\/strong><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

          Application Points for Vietnamese Factories<\/h4>\n
            \n
          • Scenario Planning for Peak Demand (Pre-Tet \/ Black Friday)<\/strong>: Share production plans for each product and forecast demand for A-rank items 2-3 months in advance.<\/li>\n
          • KPI for Redundancy Days due to Port Congestion and Road Traffic<\/strong>: Calculate a ‘Port Congestion Risk Index’ based on past data and reflect it as a coefficient in the lead time.<\/li>\n
          • Standardize Quality Gates for Local Suppliers<\/strong>: When increasing the local procurement ratio, apply ISO 2859-1 sampling inspection to local products as well to suppress quality variations.<\/li>\n<\/ul>\n

            By combining these measures, it is possible to minimize lead time extensions due to demand “peaks and valleys” and prevent line stoppages without holding excess inventory.<\/p>\n

            Risk Diversification through Supplier Consolidation and Multi-Sourcing<\/h3>\n

            In today’s globalized world, suppliers for screw procurement have diversified to include Japanese, local, and Chinese companies. As the number of suppliers increases, management load and costs grow at an accelerating rate. On the other hand, reliance on a single supplier can be fatal in the event of geopolitical risks or quality problems. This section explores how to balance the conflicting themes of “consolidation and diversification”<\/strong> to find the optimal balance between cost and risk.<\/p>\n

            Cost Benefits of Supplier Consolidation<\/h4>\n
              \n
            1. Unit Price Reduction through Economies of Scale<\/strong>: Consolidating order volumes increases purchasing power, with an expected unit price reduction of up to 10-15%<\/strong>.<\/li>\n
            2. Simplification of Ordering and Inspection Processes<\/strong>: Reducing the number of purchase orders (P\/O) from 50 to 20 per month can lead to cost cuts of around 1 million JPY annually just from administrative labor and bank transfer fees.<\/li>\n
            3. Reduction of Inspection and Logistics Costs<\/strong>: By consolidating screws with common specifications into the same lot, you can reduce the number of witness inspections and increase the ratio of full container load (FCL) shipments.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
              <\/td>\nBefore Consolidation<\/strong><\/td>\nAfter Consolidation<\/strong><\/td>\nReduction Rate<\/strong><\/td>\n<\/tr>\n
              Number of Suppliers<\/td>\n25 companies<\/td>\n12 companies<\/td>\n52%<\/td>\n<\/tr>\n
              Annual Purchase Orders<\/td>\n600<\/td>\n240<\/td>\n60%<\/td>\n<\/tr>\n
              Average Unit Price<\/td>\n5.5 JPY<\/td>\n4.9 JPY<\/td>\n11%<\/td>\n<\/tr>\n
              Annual Transaction Cost*<\/td>\n9.2 million JPY<\/td>\n6.4 million JPY<\/td>\n30%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

              *Transaction Cost = Sum of ordering\/inspection admin + international\/domestic transport + receiving inspection costs (internal estimate)<\/p>\n

              As shown, consolidating non-core item suppliers to gain economies of scale<\/strong> leads to direct cost improvements.<\/p>\n

              Geopolitical Risk and Supply Chain Resilience<\/h4>\n

              However, relying on a single source even for critical safety components carries the risk of procurement disruption from external shocks, such as:<\/p>\n

                \n
              • Navigation restrictions in the South China Sea<\/strong><\/li>\n
              • Additional tariffs due to US-China trade friction<\/strong><\/li>\n
              • Sudden spikes in raw material nickel prices<\/strong><\/li>\n<\/ul>\n

                Therefore, the following multi-sourcing strategy<\/strong> is recommended:<\/p>\n

                  \n
                • Dual Sourcing for Critical Parts<\/strong>: Secure at least two certified suppliers (1 domestic \/ 1 overseas) for A-rank items, with a 60:40<\/strong> order distribution during normal times. Include contract clauses that allow switching to a backup supplier within 24 hours in an emergency.<\/li>\n
                • Regional Diversification Model<\/strong>: Form a network of suppliers with manufacturing bases in the ASEAN region, such as Thailand and Indonesia, and select the optimal port considering transport lead times and tariff policies.<\/li>\n
                • Cross-Docking and Milk Run Delivery<\/strong>: Consolidate products from multiple suppliers at a hub warehouse and deliver just-in-time to each factory. This compresses transport costs through “consolidated shipping” while maintaining risk diversification.<\/li>\n<\/ul>\n

                  Case Study: Semiconductor Equipment Manufacturer (Vietnam Factory)<\/strong><\/p>\n

                    \n
                  • Procured A-rank high-strength screws from two companies in China and Vietnam. Normal period: 70% China, 30% Vietnam.<\/li>\n
                  • In early 2025, container delays occurred on the South China Sea route, delaying transport between China and Vietnam by +10 days.<\/li>\n
                  • Immediately switched the Vietnam supplier ratio to 90%. Line stoppage was avoided as a two-week supply was secured in VMI stock.<\/li>\n
                  • As a result, no additional transport costs were incurred, and an OTD of 99.2% was maintained.<\/li>\n<\/ul>\n<\/blockquote>\n

                    As this case shows, by incorporating backup production capacity<\/strong> and inventory buffers<\/strong> into contracts, risks can be minimized even when geopolitical events occur.<\/p>\n

                    Tips for Balancing Consolidation and Diversification<\/h4>\n
                      \n
                    • Portfolio Analysis<\/strong>: Plot suppliers by unit price, quality, and risk score to classify candidates for consolidation and those to be maintained for diversification.<\/li>\n
                    • Frame Agreement + Spot Orders<\/strong>: Fix prices with an annual frame agreement while leaving room for spot orders to respond flexibly to supply and demand fluctuations.<\/li>\n
                    • Continuous Improvement Program (CIP)<\/strong>: Operate QC circles across suppliers to share process improvements, achieving both cost reduction and quality improvement.<\/li>\n<\/ul>\n

                      Based on these measures, let’s build a system that enhances supply chain resilience<\/strong> while maximizing cost benefits.<\/p>\n

                      Real-Time Visualization through Warehouse and Transport Digitization<\/h3>\n

                      The bottleneck in parts logistics, including screws, stems from the inability to know “where what is, and how many” at any given moment. Paper slips and Excel management lead to delayed information updates, causing picking errors and delivery delays. This is where the combination of WMS (Warehouse Management System), TMS (Transport Management System), and IoT<\/strong> is gaining attention.<\/p>\n

                      Traceability with WMS\/TMS\/IoT<\/h4>\n\n\n\n\n\n\n
                      Technology<\/strong><\/td>\nMain Functions<\/strong><\/td>\nExpected Effects<\/strong><\/td>\n<\/tr>\n
                      WMS<\/td>\nReal-time management of receiving\/shipping, inventory, and locations<\/td>\n\u25b270% in stocktaking labor, 99.9% inventory accuracy<\/td>\n<\/tr>\n
                      TMS<\/td>\nVisualization of vehicle dispatch plans and transport progress, cost analysis<\/td>\n+15pt in loading rate, \u25b210% in transport costs<\/td>\n<\/tr>\n
                      IoT Sensors\/RFID<\/td>\nAutomatic acquisition of temperature, humidity, impact, and location data per screw box<\/td>\nEarly detection of quality issues, \u25b290% in tracking time<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                      Since screws are often mixed in various sizes and lot numbers, attaching RFID tags (UHF band) to each box and using gate antennas to automatically recognize inbound and outbound shipments is effective. When linked with a TMS, the status can be updated to “shipped” the moment a truck passes through the gate, and the estimated time of arrival can be automatically recalculated based on the delivery route and traffic information.<\/p>\n

                      Implementation Effects (Automotive Parts Manufacturer, Hanoi)<\/h5>\n
                        \n
                      • Monthly Picking Errors: 150 cases \u2192 12 cases (\u25b292%)<\/strong><\/li>\n
                      • Delivery Delays: 20 cases\/month \u2192 3 cases\/month (\u25b285%)<\/strong><\/li>\n
                      • Traceability Response Time: Average 4 hours \u2192 15 minutes<\/strong><\/li>\n<\/ul>\n

                        Seamless Integration of Factory-Logistics-Supplier via API<\/h4>\n

                        Even if multiple systems are introduced, true real-time visualization cannot be achieved if they are siloed. Therefore, data flows like the following are constructed using RESTful APIs<\/strong> or EDI (ANSI X12\/EDIFACT)<\/strong>.<\/p>\n

                          \n
                        1. Supplier \u2192 WMS<\/strong>: Advance Shipping Notices (ASN) are automatically registered via API.<\/li>\n
                        2. WMS \u2194 TMS<\/strong>: Shipping instructions and delivery statuses are synchronized bidirectionally. In case of rescheduling, the warehouse picking order is automatically updated.<\/li>\n
                        3. TMS \u2192 Production Management System<\/strong>: The Estimated Time of Arrival (ETA) is fed back to the production plan to optimize lineside inventory.<\/li>\n
                        4. BI Dashboard<\/strong>: Data is streamed to Power BI\/Tableau via API to display OTD\/inventory turnover in real-time.<\/li>\n<\/ol>\n

                          TIP for Vietnam’s Local Communication Conditions<\/strong>: In areas with unstable mobile communication, a design that temporarily stores data with the MQTT protocol + local cache and sends it in bulk upon reconnection is recommended.<\/p>\n

                          Step-by-Step Implementation Roadmap<\/h5>\n
                            \n
                          1. Visualize Current Business Flow<\/strong>: Map the value stream from receiving\/shipping to vehicle dispatch and goods receipt to identify information delay points.<\/li>\n
                          2. Select Digitization Use Cases<\/strong>: Start with areas with high ROI, such as RFID implementation or automated vehicle dispatch.<\/li>\n
                          3. Conduct PoC (Proof of Concept)<\/strong>: Perform a small-scale verification on 1-2 lines and 1 warehouse, measuring KPIs (picking accuracy, on-time delivery rate).<\/li>\n
                          4. Company-wide Rollout and API Integration<\/strong>: Horizontally deploy the successful model and gradually integrate API links with ERP and production management systems.<\/li>\n
                          5. Continuous Improvement (CI)<\/strong>: Accelerate the improvement cycle by running the PDCA cycle based on real-time data from the dashboard.<\/li>\n<\/ol>\n

                            The goal of digital technology is not the implementation itself; the ROI is maximized only when a data-driven decision-making culture<\/strong> takes root. The key to success is to start small, confirm results quickly, and expand incrementally.<\/p>\n

                            Automation of ISO\/JIS Screw Standard Management and Quality Assurance<\/h3>\n

                            Screws that look identical can have different detailed specifications, such as thread angle, pitch, and plating thickness<\/strong>, with multiple standards like JIS B1180 and ISO 898-1 coexisting. If the wrong standard is used and sent to the assembly line, it can cause component interference or fastening failures, with reports of re-procurement costs + line stoppage losses increasing the original cost by 2-5 times<\/strong>.<\/p>\n

                            Process Design to Approach Zero Standard-Related Errors<\/h4>\n\n\n\n\n\n\n
                            Measure<\/strong><\/td>\nDescription<\/strong><\/td>\nEffect<\/strong><\/td>\n<\/tr>\n
                            Integrated Standard Master DB<\/td>\nCentralize screw standard information scattered across ERP and PLM, linking ISO\/JIS codes to each part number.<\/td>\n\u25b290% in incorrect ordering rate<\/td>\n<\/tr>\n
                            2D Code Labeling<\/td>\nPrint a DataMatrix on shipping boxes containing JIS\/ISO codes + torque settings.<\/td>\n\u25b295% in picking errors<\/td>\n<\/tr>\n
                            Electronic Approval Workflow<\/td>\nThe quality assurance department electronically signs off on standard changes, which are then automatically notified to suppliers.<\/td>\n\u25b280% in standard change lead time<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                            Quality Stabilization with Automated Measurement and AI Inspection<\/h4>\n

                            Traditional inspection with ring gauges and pitch gauges depended on operator skill, and sampling inspection was limited to 1-3%. In recent years, by combining cameras \u00d7 AI<\/strong> and non-contact 3D scanners<\/strong>, it is possible to maintain tact time even with 100% inspection<\/strong>.<\/p>\n

                            Implementation Case: OHTA VIETNAM \u00d7 Japanese Automotive OEM<\/strong><\/p>\n

                              \n
                            1. Measured screw heads and threads with 0.01mm accuracy using a 3D line sensor (0.6 seconds per screw).<\/li>\n
                            2. An AI model compared dimensions against JIS\/ISO tolerances and made a real-time OK\/NG judgment.<\/li>\n
                            3. NG products were automatically ejected, and image and dimensional data were saved to the cloud.<\/li>\n<\/ol>\n

                              Results<\/strong>:<\/p>\n