Screws not only “connect” products but are also the lifeline that supports the entire production line. However, with a vast number of types and sizes, even a stockout of a screw costing just a few yen can halt the line, potentially leading to delivery delays and increased costs. This article explains how to strike a balance to manage such screw inventory “without stockouts and without holding excess.”

The intended readers are those in charge of production control, material purchasing, and on-site supervision. We have covered concrete measures directly applicable to practice, such as reducing man-hours for inventory counting that is a daily headache on the manufacturing floor, automated ordering using IoT, and cost reduction through procurement in Vietnam.

By the time you finish reading this article, you should have a systematic understanding of screw inventory management and a checklist that you can try on-site immediately. Now, let’s take the first step toward optimal inventory.

What you can learn in this article

Even if a single screw costs only a few yen, a stockout can bring the entire production line to a halt, leading to significant opportunity losses. For example, in automotive parts factories, it is not uncommon for line stoppage costs to amount to several hundred thousand yen per minute. There are also latent risks that are difficult to quantify in monetary terms, such as customer contract penalties and brand damage due to delivery delays.

On the other hand, excess inventory also ties up capital unnecessarily and puts pressure on warehouse space and inventory counting man-hours. Screws tend to have a vast number of items due to differences in size and material, and if not properly managed by location, the risk of mix-ups and contamination defects increases. To suppress both “line stoppages due to stockouts” and “cost increases due to excess inventory,” quantitative KPI management is essential.

By visualizing these KPIs on a dashboard and narrowing down the key management targets with ABC analysis, high improvement effects can be expected even with limited resources. For example, one electronics manufacturer increased the inventory turnover rate for “A” rank items (top 20% of annual consumption value) from 4 to 9 times, reducing inventory value by 35% annually. The stockout rate was also reduced from 0.8% to 0.2%, suppressing production line stoppage troubles to zero.

Screws are subdivided into hundreds or even thousands of items by “size × material × surface treatment,” so managing everything with the same level of precision will cause both management man-hours and costs to soar. An effective method for this is to create a matrix of inventory using the two axes of ABC analysis and XYZ analysis.

By combining them as an ABC × XYZ Matrix, priorities such as “AX = high value, stable demand” and “CZ = low value, irregular demand” become clear at a glance. An electronics manufacturer supported by GIS Ohta Vietnam reduced inventory value by 28% and shortened inventory counting time by 45% by introducing this matrix.

To reduce inventory while preventing stockouts, it is essential to explicitly define the order quantity and order timing with formulas. A representative combination is EOQ (Economic Order Quantity) and ROP (Reorder Point).

By tuning the EOQ-ROP method for each ABC-XYZ rank, it becomes possible to manage with nuance, such as “maintaining a larger safety stock for AX rank screws” and “minimum stock + spot ordering for CZ rank screws.” As a result, there are reported cases where the number of monthly orders was reduced by 40% while keeping the stockout rate at 0.3%.

Source: Lokad, OpenSCM

SmartMat Cloud uses a platform scale-type IoT weight sensor placed under the screw box to transmit weight changes in 1g units to the cloud at 10-second intervals. By registering the standard weight per box, the inventory converted to a piece count is automatically updated, reducing manual inventory counting man-hours by up to 80%. By setting an automatic alert at a threshold of “remaining quantity ○%”, items at risk of stockout are highlighted, and notifications are sent to the person in charge via email or LINE. At automotive parts manufacturer Company A, this was introduced for 400 items, achieving zero stockouts for 12 consecutive months and reducing inventory counting time to 1/4.

The “remaining inventory/recommended order data” generated by SmartMat Cloud can be automatically linked to an ERP via CSV or REST API. In the case of Aladdin Office, which is often adopted by mid-sized manufacturing companies, using the real-time API option that immediately reflects receiving and shipping data allows for the automatic generation of purchase orders. In an implementation case, the administrative man-hours for order processing were reduced from 40 hours/month to 8 hours/month, and inventory value was also compressed by 15%. Note that the standard version mainly uses batch integration, so for real-time functionality, considering an API license or RPA integration is advisable.

Source: SmartMat Cloud, Aladdin Office

As a manufacturing hub in Asia alongside China and Thailand, Vietnam has excellent cost competitiveness, with labor costs about 1/5 of Japan’s and electricity unit prices about 40% lower. Furthermore, in the northern Haiphong area and near Ho Chi Minh City in the south, where Japanese companies have concentrated, there are over 100 specialized screw manufacturers compliant with JIS and ISO, making it possible to procure special materials and small-diameter taps locally in a single batch.

Based on these conditions, GIS Ohta Vietnam proposes a hybrid procurement scheme, such as “local mass production and sea transport for A-rank items with a monthly demand of 1,000 pieces or more” and “domestic emergency stock for Y-group items (large seasonal fluctuation).” On average, client companies have achieved a 17% reduction in procurement costs and a 22% reduction in inventory value.

GIS Ohta Vietnam, with its local network in Vietnam, offers a unique solution that provides one-stop support for “Procurement + Inventory + Quality.”

In an implementation case, electronics manufacturer Company B transferred its monthly inventory of 800 screw items to GIS’s VMI, reducing annual inventory counting work by 150 hours and improving the stockout avoidance rate from 99.8% to 100%. Furthermore, through kitting, they have eliminated fastening defects due to line mistakes.

Source: Ohta Vietnam

Evaluate the following 10 items with Yes/No and extract the unachieved items as priority improvement points.

If the achievement rate of the checklist is less than 80%, there is a high risk of screw inventory stockouts/surpluses. Monitor the achievement rate each period and quantitatively confirm the effects of improvements.

By implementing these measures in stages and running a PDCA cycle while visualizing KPIs on a dashboard, screw inventory will transform into a “source of cost reduction.” First, diagnose the current situation using the checklist in this article and start with the highest priority issues.

Conclusion

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