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Hebei Daily | Shisi Pharmaceutical: Unlocking the Potential of “Industrial AI”

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Media Reports

发布时间：2024-05-17

【概要描述】 The order management system and the logistics and transportation system are slated for launch soon, and preliminary research on a supplier interaction platform has already begun… Like piecing together a jigsaw puzzle, Shisi Pharmaceutical is steadily building an increasingly comprehensive digital ecosystem. Meanwhile, digital transformation is opening up vast new possibilities for the company as it explores the application of “industrial AI.”

Hebei Daily | Shisi Pharmaceutical: Unlocking the Potential of “Industrial AI”

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Due to the unique characteristics of the pharmaceutical industry, recording and storing drug-related data and identifying the “optimal solution” for order scheduling and production planning have long been major challenges facing Shijiazhuang No. 4 Pharmaceutical Group (hereinafter referred to as “Shi Si Yao”).

By building its own private cloud, Shisi Pharmaceutical has successively developed an intelligent collaborative system for production, supply, and sales, as well as a manufacturing execution system. These initiatives have not only addressed the pain points in production scheduling but have also made it possible to transition from paper-based to electronic batch records for pharmaceutical products.

The order management system and the logistics transportation system are slated for launch soon, and preliminary research on a supplier interaction platform has already begun… Like piecing together a jigsaw puzzle, Shisi Pharmaceutical is steadily constructing an increasingly comprehensive digital blueprint. Meanwhile, digital transformation is opening up vast new possibilities for the company as it explores the application of “industrial AI.”

The “Digital Brain” for Processing Vast Amounts of Pharmaceutical Industry Data

Bottle-making and pharmaceutical liquid filling, among other processes, flow seamlessly thanks to the interconnected conveyor system, while robotic arms move effortlessly between production lines, executing every task with precision and efficiency… In this vast production facility, there is no sign of the bustling workforce typical of traditional manufacturing floors.

On May 10, the digital and intelligent upright soft-pack infusion production workshop at Shisi Pharmaceutical unveiled a new vision of smart manufacturing.

Dilution, bottle preparation, filling, sterilization, visual inspection, boxing—due to the unique nature of pharmaceutical products, regulations require that production-process parameters be retained at every stage for each batch. Shisi Pharmaceutical’s digitally intelligent, upright soft-pack infusion production workshop is home to China’s largest single-line large-volume infusion production facility, with a daily capacity of 2 million bottles. Such massive production volumes, in turn, generate an enormous volume of data that must be collected, recorded, and archived.

“Material information, equipment information, production information, environmental information, and material balance information—just the single step of formulation involves production parameters across these five major areas, totaling more than 70 items,” explained Duan Guangqian, Director of the Digital and Intelligent Vertical Soft-Pack Infusion Production Workshop at Shisi Pharmaceutical. “With the realization of production-line automation, the actual formulation operations have largely been taken over by machines; however, the recording of production parameters still has to be done manually, which is both time-consuming and labor-intensive. The key challenge is that every batch produced requires a corresponding set of parameter records.”

Parameter recording has long been a major pain point for pharmaceutical companies.

Wang Yang is a formulation operator in the upright soft-pack infusion production workshop at Shisiyao, where digital and intelligent technologies are being implemented. This position operates on a three-shift system, and during each 8-hour shift, Wang Yang is responsible for recording the production parameters for two to three batches of medication.

“These production parameters not only involve massive amounts of data, but also require painstaking attention to detail when recording—some parameters are exceptionally long, stretching nearly 20 digits. By the end of a shift, your eyes are absolutely exhausted,” said Wang Yang.

In mid-May, the Shisi Pharmaceutical digital and intelligent upright soft-pack infusion production workshop is set to undergo a transformation: these parameter records will no longer rely on manual handwriting.

The unsung hero behind this transformation is Shisiyao’s “digital brain” for the production process—the Manufacturing Execution System.

Under the precise “command” of this “digital brain,” staff只需 enter the relevant instructions into the system, and various devices and robots can respond instantly, achieving autonomous coordinated operation.

Moreover, the operation of this system has made it possible to transition drug batch records from paper-based to electronic format.

“Starting in early March of this year, we began testing this manufacturing execution system on our production lines while simultaneously conducting the 4Q validation—widely adopted in both domestic and international pharmaceutical industries during equipment qualification. Currently, this validation has entered the final PQ phase,” said Zhou Changtao, Executive Deputy General Manager of the Information Management Center at Shisi Pharmaceutical.

However, Zhou Changtao explained that during the trial run, the system will continue to use both paper and electronic records in parallel, with the aim of thoroughly validating the accuracy and reliability of the electronic records by comparing them with their paper counterparts. Therefore, Wang Yang and his colleagues will need to continue manually recording data for some time yet.

“There is currently no precedent in our province for transitioning drug batch records from paper-based to electronic format,” Zhou Changtao stated. He added that, upon completion of this pilot run, Shisi Pharmaceutical will coordinate with the relevant authorities to conduct an assessment. The assessment will cover whether the procedures for acquiring data from equipment and the frequency of such data collection—key aspects of the electronic record-keeping process—are conducted in compliance with regulatory standards, as well as the stability and reliability of the electronic system itself.

Transforming “manual fire-fighting” into “optimal scheduling”

“Look, on this chart, each production line is color-coded, with detailed annotations indicating the specific product being manufactured and the corresponding production schedule.”

Opening a chart cluttered with colorful blocks at random, Hao Dongliang, Deputy General Manager of the Information Management Center at Shisi Pharmaceutical, pointed to the chart and explained: “Each row represents the production schedule for a single manufacturing line. For example, from March 4 to 6, the 100 mL specification of 0.9% sodium chloride injection was produced continuously on Production Line No. 20 for 72 hours. Immediately afterward, the same line switched over to produce another product—500 mL specification of 0.9% sodium chloride injection—for a total of five days.”

Hao Dongliang pointed to another section of the chart: although the product was manufactured over a total of eight days, it was completed sequentially on seven production lines.

“This kind of production scheduling is the order-planning result generated by the intelligent supply-chain collaboration system we have deployed,” explained Hao Dongliang.

Order scheduling used to be a major challenge for Shisi Pharmaceutical.

Shisi Pharmaceutical operates more than 20 production lines, covering some 600 to 700 drug specifications, with a monthly output of over 200 million bottles or bags. Due to the inherent characteristics of pharmaceutical products, each production line must undergo either a major or minor cleaning and sanitization when switching between different product specifications; the former may take one to two hours, while the latter requires complete disassembly of equipment components for thorough cleaning.

Beyond these considerations, production scheduling must also take into account the range of product types each production line can manufacture, as well as the coordination among procurement, warehousing, manufacturing, quality control, and sales—processes that involve such vast amounts of data that they far exceed the cognitive limits of the human brain.

Faced with massive volumes of data, order scheduling has become a challenge that cannot be solved simply by relying on a sense of responsibility or traditional rules and regulations.

Li Aihua is a production scheduling planner at Shisi Pharmaceutical, whose primary responsibility is to develop and schedule production plans.

“Firefighter” was once how Li Aihua defined her professional role.

“The production plan for next week needs to be finalized by this Wednesday, and then distributed to all departments,” Li Aihua said. Yet as soon as the plan is released, calls, WeChat messages, and QQ notifications from colleagues start pouring in one after another.

The difficulty lies in the fact that the issues reported by each department are intricately interconnected.

“All of our production activities are driven by sales orders. However, orders can come in at any moment, and the various functional departments don’t always manage to coordinate seamlessly. Very often, the sales team is pressing for new orders to kick off production, only to find that the production department lacks sufficient raw materials; meanwhile, the procurement team, in trying to source those materials, may encounter stockouts, and the warehouse may discover that the newly purchased supplies simply won’t fit.”

With no other choice, Li Aihua had to keep tweaking the production schedule right up until the weekly Friday production-sales coordination meeting. In fact, the meeting often devolved into a tense standoff over how to prioritize and allocate orders.

Li Aihua has been working as a production scheduling planner for more than seven years. In the early years, this kind of “frustrating” situation occurred almost every week, repeating itself over and over.

“Because each department operates as a data silo, it is indeed challenging to ensure precise and efficient coordination among them.” Incomplete, inaccurate, and non-real-time data are the root causes of this predicament, a reality that Li Aihua understands all too well.

In the past, in order to determine the remaining stock of a particular raw material, the procurement department not only had to check the warehouse inventory but also often had to visit each production workshop individually to assess the remaining quantities, so as to calculate how much more material needed to be purchased. Moreover, when placing orders, they had to consider whether suppliers could deliver the materials on time.

However, these efforts have yielded only minimal results compared with the vast and complex “black box” of data.

“Everyone was ‘putting out fires’ manually, just gritting our teeth and pushing forward week by week,” Li Aihua said. At the time, the biggest concern was sudden, urgent orders, because even the smallest change could set off a chain reaction that left the entire production–supply–sales chain in a critical situation.

However, departments are now relieved: previously, the group would draft a production plan for the following week every Wednesday and revise it at least three times weekly; now, with the intelligent supply–production–sales collaboration system, a single “run” in just 20 minutes can generate a four-month production schedule.

Supported by advanced algorithms, the intelligent production–supply–sales collaboration system leverages existing business systems to capture and integrate data across inventory, procurement, sales, shop-floor equipment, and capacity, effectively acting as a “virtual” order scheduler that identifies the optimal solution for coordinating all stakeholders.

“The final scheduling outcome may not necessarily be the most efficient when viewed from the perspective of a single production line alone. However, when we take into account the combined production capacities of all lines and the coordinated flow across every stage of the process, the resulting arrangement will invariably be the optimal one,” explained Hao Dongliang. “It’s akin to using a car navigation system: you input each vehicle’s characteristics and real-time data, along with traffic-light statuses on the road, into a model; you factor in all road conditions and other potential variables; and then the system identifies the single, optimal route.”

According to estimates, since its official launch in September 2023, the intelligent production–supply–sales collaboration system has reduced plan preparation and modification time at Shisi Pharmaceutical by 50%, increased effective capacity utilization by 10%, improved on-time product availability by 15%, and significantly boosted inventory turnover.

“Industrial AI” Stitched Together Piece by Piece

Recently, the Information Management Center of Shisi Pharmaceutical has been busy conducting final debugging on a new system—the Order Management System—and the system is scheduled to go live at the end of May.

“The Order Management System primarily focuses on receiving customer orders from external sources and tracking the execution status of those orders. To complement this system, we have also developed a logistics and transportation system that visualizes vehicle dispatching and the delivery of goods to customers. Together, these two systems create a complete closed-loop order fulfillment process,” explained Zhou Changtao. He added that the Production Execution System and the Intelligent Collaborative System for Production, Supply, and Sales are more geared toward internal management. Building on this foundation, Shisiyao has further extended its digital reach outward.

In addition to the soon-to-be-launched order management system and logistics transportation system, Shisi Pharmaceutical also plans to develop an interactive platform for suppliers. Once operational, Shisi Pharmaceutical will be able to place purchase orders directly through the system, while suppliers can respond and manage their commitments on the same platform. Together, the two parties will operate on a Taobao-like marketplace that enables end-to-end traceability of the entire order fulfillment process.

Like piecing together individual puzzle fragments, Shisi Pharmaceutical aims to construct a comprehensive digital blueprint.

The ultimate goal is to ensure that all business operations—both external interactions with customers and suppliers, and internal connections among equipment and personnel—are conducted on digital platforms and systems, driven by digital transformation, so that every activity can be digitally traced and simulated.

“In this sense, digitalization represents a higher level of digital transformation,” Hao Dongliang explained. He noted that many enterprises have implemented enterprise resource planning systems to support their digital initiatives, with these systems further segmented into numerous specialized modules tailored to specific production needs. However, the data granularity of such systems tends to be relatively coarse; from a management perspective, the information they provide is primarily outcome-based.

This severely constrains the effectiveness of digitalization in enterprise management.

Data granularity refers to the level of detail in the data.

“When data is aggregated at a coarse granularity, managers only receive a simplified snapshot and lack visibility into the data’s underlying generation process. To gain deeper insights, they must either convene meetings to hear reports or drill down layer by layer—starting with the general manager asking the deputy general manager, who in turn queries the department heads, and so on, all the way to the operational level…” Hao Dongliang explained. However, if the data fed into the system is more granular and updated more frequently, the situation changes dramatically.

“For example, when managers see sales growth data, a simple query in the system reveals which products are selling the most and which departments are contributing the most—only then can we truly say that digital management has been achieved,” said Hao Dongliang.

According to Su Zhongliang, Deputy General Manager of the Information Management Center at Shisi Pharmaceutical, digitalization, at its core, is about leveraging data to create value.

Su Zhongliang recognizes the potential of digitalization to help enterprises achieve deep reductions in resource consumption.

“By leveraging data, we will be able to conduct line-by-line comparisons in the future, using modeling and algorithms to analyze differences in energy consumption and efficiency between production lines and identify areas where optimization and improvement are possible,” said Su Zhongliang. “As long as we have sufficient data at a sufficiently granular level, we can even perform horizontal benchmarking against industry peers to pinpoint gaps and address shortcomings.”

Hao Dongliang, on the other hand, places greater emphasis on the “chemical reaction” that emerges from the interplay of data and algorithms.

“The finer the data granularity, the smarter the model, and the more precise and realistic the optimal solution derived from the data.” Hao Dongliang hopes to leverage data and algorithms to build an increasing number of “industrial AIs” like the intelligent supply–production–sales collaboration system, enabling them to continuously coordinate and optimize for enterprises and deliver ever more “optimal solutions” for sustainable growth.

Reporter's Observation

Digitalization Drives Transformation in Corporate Operations and Management

By implementing a Manufacturing Execution System, key process parameters can be automatically recorded, which not only reduces labor costs but also enhances the accuracy and reliability of data; furthermore, deploying an intelligent production–supply–sales collaboration system leverages algorithms to optimize production scheduling, thereby enabling efficient cross-departmental collaboration…

Shisiyao’s digital transformation fully demonstrates how modern technology can empower enterprises to achieve refined management and efficient operations, while also highlighting the core value of digitalization in business operations: endowing every process with “measurability” to enable comprehensive, end-to-end, granular management.

Today, thanks to digital technologies built on the cloudification of industrial equipment, an increasing number of enterprises like Shisiyao are leveraging real-time data that captures every stage of production, supply, and sales—and even every individual piece of equipment—enabling them to pursue efficiency and cost savings down to the smallest detail and to practice meticulous cost management.

Precisely for this reason, in the new digital landscape, companies are no longer competing solely on product quality and production efficiency; they are also engaged in fierce competition in data analytics, resource allocation, and supply-chain management.

Replacing traditional experience-driven decision-making with data-driven decision-making, and seeing the shift from conventional hierarchical structures to flatter, more agile networked architectures—these transformations demonstrate that digitalization is not merely a technological upgrade; it is, above all, a fundamental reinvention of business philosophy.

Digital transformation is not achieved overnight; it requires iterative upgrades as well. Experts point out that the inevitable stages of enterprise digital transformation include moving from manual operations to system development, then to system integration and interconnection, followed by data-driven operations, and ultimately leveraging data to inform decision-making.

As technology matures, the cost of digital transformation is steadily declining, enabling more enterprises to participate in this transformative journey and opening up greater possibilities for “digital intelligence” for every organization willing to embrace change.

(Originally published in Hebei Daily)

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