Supply Chain Management with Digital Transformation

Supply Chain Management with Digital Transformation
Supply Chain Management with Digital Transformation

Looking around the world at the locations of LNG terminals (Figure 1) and other major processing plants, they tend to form in clusters. Common considerations include proximity to port facilities, customer locations and transportation access to rail and inland waterways. What this reflects is the importance of effective supply chains and logistics. The additional costs and operational complications of a poorly selected site can make a facility unprofitable and even lead to closure. In this article, we’ll examine supply chain management (SCM) in general, and how it applies specifically to the operation of a single LNG terminal.

Figure 1: LNG terminals depend on critical supply chains to operate profitably.


Terminals, refineries and chemical processors operate continuous processes and must therefore maintain uninterrupted raw material supplies (feedstocks) coming in and finished products going out. If either flow fails, it could cause a serious disruption to the entire supply chain.
 
This is further complicated by variability of said feedstocks, along with potential requirements for different grades of finished products. Not only does the feedstock have to be on hand in sufficient quantities, it must also be the right kind and have the correct characteristics so the plant can process it effectively and profitably to create the products customers are demanding.
 
Effective SCM has always been a challenge, but it has become more complex than ever due to ever faster market dynamics on both ends. Natural gas processors, oil refiners, and petrochemical plants must account for these dynamics on a daily basis as feedstock sources can change in an instant, as can customer demands.
 

Coping with reality

Traditional SCM methods are typically fragmented by department and minimally coordinated. Sales produces forecasts, but these don’t always have the degree of accuracy needed to guide planning. Demand for Grade 1 product called for by the forecast may not coincide with production planning, leaving all the product storage space filled when orders for Grade 2 call for a switchover. The plant has to wait for demand to catch up, while having to spend more on storage due to the mismatch. The same can happen with feedstocks. Inadequate coordination can result in having the wrong feedstock on hand, filling up whatever storage space is available.
 
This kind of confusion happens because there is no mechanism to tie all the areas together (Figure 2)
so they can be coordinated effectively. There are forecasts, schedules, and reports circulating—but they are either untimely or do not reflect the big picture. Such snapshots leave planning ineffective, driving up costs and hampering timely customer deliveries. Storage of poorly timed feedstocks and finished products results in higher inventory carrying costs and ineffective use of capacity.

Figure 2: Manual supply chain management methods are fragmented, whereas digital transformation makes it possible to tie multiple elements into one integrated plan.


Plants may point to their automated systems as a possible SCM solution, but these often prove to be little better, and are sometimes worse, than the manual systems they replaced. Many of these automated systems simply preserve longstanding fragmentation, lacking the overall coordination necessary to attain enterprise-wide goals. Efforts to bridge gaps vary in effectiveness due to differences in methodology and hardware. Systems without sufficient concern for cybersecurity can introduce vulnerabilities and attack vectors.
 
Ultimately, these and other types of existing systems may do little more than move longstanding manual methods onto computers, without improvements in overall effectiveness. Where coordination should create a seamless environment, gaps remain, so there is little advancement. Fortunately, Yokogawa can provide better software platforms (Figure 3) capable of delivering vastly improved performance.

Figure 3: Digital transformation avoids dependence on manual systems and key people for supply chain management


By building out solutions on a single platform, simple management of supply chains is transformed into optimization.
 

Management becomes optimization

If asked to define effective SCM, most managers would characterize it as selecting the best feedstocks possible at the best price to manufacture the slate of products demanded by customers. Everything should be onsite in a timely manner to maintain production schedules and maximize output. Those are all desirable goals, but in many ways, they don’t go far enough. Plants should strive for more, using advanced tools to achieve true optimization.
 
Specific competencies for supply chain optimization include:

  • Term Contract Planning: Evaluate long-term contract obligations from commercial and economic perspectives.

  • Supply Chain Planning: Optimize the hydrocarbon supply chain for short-, mid-, and long-term, and for strategic time horizons.

  • Price Deck Formulation: Generate price forecasts based on optimization boundaries and time horizons for feedstock and products.

  • Supply Chain Scheduling: Schedule optimized operations over time, including process inventory and blending, taking logistical constraints into account.

  • Commercial Contracting: Develop and negotiate favorable and competitive contract terms for feedstocks and products.

  • Inventory Management: Measure and reconcile the amount of raw materials consumed and products made to produce an accurate material balance through production accounting and loss measurement.

  • Dispatch Management: Complete processes digitalization, fully automated from sales order to invoice.

 
Developing these competencies requires digitalizing operations in all phases from raw materials to finished products. This supports optimization in all areas, avoiding the silos and gaps hampering traditional approaches. End-to-end digitalizing makes it possible to identify hidden costs in the chain, the waste they cause, and lost profitability.
 

LNG tank operations scheduling

To provide some real-world insight, consider an LNG terminal (Figure 4). The site must stage incoming tankers for unloading and route their products to the appropriate storage tanks and shipping points.

Figure 4: Simple process diagram of LNG regasification terminal.


Scheduling involves many daily decisions related to the transportation, storage and processing of feedstocks and products—with each critical to the effective implementation of the plan and its effect on production efficiency and enterprise profitability.
 
Schedulers and other personnel at LNG terminals usually try to create one-month tank operations schedule based on the current inventory, ship schedule, and demand forecast.  However, most of the time, data gathering is done manually, and the schedule is derived using multiple spreadsheets.
 
Decisions include but are not limited to:

  • Which tanks an incoming shipment should be routed to for transit storage.

  • How to route product from source tanks to shipping points.

  • Which inter-tank transfers should be scheduled to adjust volumes and heat value.

 
Considerations include dealing with constraints such as tank and equipment capacity, along with quality requirements and other factors.
 
Moreover, as the estimated ship arrival dates and demand are impacted by weather and other conditions, schedulers are forced to adjust the schedule on-the-fly. As a result, it is very difficult for the schedulers to make a plan that can satisfy feasibility, security, and economics.

 
Yokogawa’s solution

Digital tools are much better at managing this kind of complexity and avoiding common problems. This takes a burden off the schedulers and allows for much faster decision making. The data is processed by a mathematical simulation model, such as Yokogawa’s KBC Visual MESA supply chain scheduling (VM-SCS, Figure 5), along with optimization algorithms.

Figure 5: Major components of an advanced supply chain management system.


VM-SCS is a leading supply chain software suite, and it can be used to turn supply chain plans into executable end-to-end schedules that account for process, tank farm, and logistical constraints. It improves integration and automation of the scheduling process, and it maximizes utilization of assets at minimum operating cost.

VM-SCS generates the receiving schedule and specifies jetty position, unloading order, and tank assignments. Shipping pumps are assigned for custody transfer. The software considers operational constraints including tank capacity, tank type, and the load on each pump. Efficiency is gained because the number of transfers and amount of LPG injection is kept to a minimum.
 

Three-pronged approach

VM-SCS has three main modules working together to solve SCM challenges.
 
Simulation Model—The simulation engine is equipped with an automatic state event detection mechanism, enabling alerting on critical disruptions situations, such as out-of-range levels and properties. The software provides future visibility through detailed simulation models of both logistic and unit operations, while maintaining constantly updated projections of inventories and material properties. It clarifies the impacts of changing conditions such as a late arriving tanker and weather problems.
 
Mathematical Programming Model—Creating higher-quality schedules calls for optimized decision making, which is very difficult when using manual planning. The scheduler may think the plan is sound, but unforeseen and undesired side effects can creep in. Optimization, on the other hand, finds a solution to optimize operations by taking all relevant factors into account. It drastically reduces the time spent on manual trial-and-error attempts, making it practical and even easy to generate an optimized schedule on a daily basis.
 
User Interface—This powerful scheduling platform includes a dynamic and flexible visual environment, including Gantt charts, trend charts, inventory grids, and process flowsheets. It also has extensive capabilities to integrate with other systems.


Optimizing an LNG terminals and its supply chain

Advanced Tank Operations Management enables planners and operators to schedule and simulate operations on an integrated supply chain topological model—including feedstock reception, tank yards, and docks—through unit operations to product shipment. Since it includes all relevant equipment, the simulation automatically propagates the effects of these operations along the supply chain, allowing identification of possible imbalances among interdependent operations.
 
This solution combines models covering logistics and production unit operations for prompt response to a wide range of conditions:

  • Availability of a raw material or feedstocks.
  • Changes in quality or characteristics of feedstocks.
  • Unit equipment condition, modifications, availability, maintenance, and personnel constraints.
  • Availability of storage.

 
This allows planners to see the effects of a change in feedstock quality—along with how it might affect unit operations, product specs, production costs, and a range of other considerations—all of which can directly affect overall plant effectiveness and profitability. The solution can project ripples caused by changes upstream and downstream along the supply chain so planners can take appropriate action.
 
The solution is designed for specific types of manufacturing processes since the plant operations sections are designed to reflect specific production units and their characteristics. The solution uses an automatic state event detection mechanism applied to control variables established by the user, which enables alerts on critical situations, such as out-of-range levels and properties.
 
This type of solution delivers financial results by reducing material cost and minimizing required raw material injection amounts.
 

Overcoming limitations of manual operation

The scheduling system with optimization deliver values by providing:

  • Improved visibility into inventory maintains product balance and identifies potential risks.

  • Standardization and automation save time and improve resource allocation.

  • Faster and better decision making validates spot opportunities.

  • Schedule integrity and consistency closes gaps between plans and actual performance.

  • Optimization of material use reduces costs.

  • Aligning materials, people, and data supports value chain optimization.

 
The technology is available today, and it can also be applied to company-wide optimization. When operational areas across an enterprise (Figure 6) find it easy to collaborate, it enables better business decisions in feedstock selection, ship dispatching scheduling, and product movements.
 

Figure 6: Coordinating operations across an enterprise improves operations.


Using an integrated solution for scheduling and optimization enables planners and schedulers to make decisions that keep both business and operational impacts in mind to deliver the maximum benefits across the enterprise.
 
All figures courtesy of Yokogawa.

About The Author


Yuji Izawa manages the supply chain management product portfolio for oil and gas industries at Yokogawa. He has 15 years of consulting and engineering experience in refinery process automation, plus an additional 8 years of management experience in R&D, marketing, sales, and delivery. He has been the project leader for new refinery offsite oil movement and blending solutions and advanced process control products, and he currently leads business development of value chain optimization with KBC for the oil and gas industry.


Did you enjoy this great article?

Check out our free e-newsletters to read more great articles..

Subscribe