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Automation
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MIN READ
October 30, 2023
October 30, 2023

Making Waves in Warehousing: The Power of Wave Picking

This article offers a comprehensive guide of wave picking: from its foundational concepts and benefits to its intersection with modern technology.

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In the intricate world of warehousing, picking strategies are crucial for efficiency and success. One strategy making notable waves is 'wave picking'. Combined with advanced systems like AutoStore, its potential is magnified. This article offers a comprehensive exploration of wave picking: from its foundational concepts to its intersection with modern technology. Dive in for a clear, concise journey through its transformative impact on warehousing.

What is wave picking? And how does it work?

Wave picking, much like its aquatic namesake, involves releasing orders in batches or "waves" for efficiency and organization. But what precisely is it, and how does it function in the context of warehouse management? Let's dive into the depths of this concept.

Origin of the wave: Understanding the rationale

Wave picking is driven by the influx of orders and the operational rhythms of the warehouse. Instead of processing orders individually or linearly as they come, wave picking groups them into manageable batches. This strategy mimics the periodic nature of waves, with each batch or "wave" of orders being processed during a particular time frame or under certain conditions.

The core mechanism: Group, release, and pick

Let's dive deeper into the main steps of wave picking. Think of it as a three-part dance: First, we group the orders; next, we release them; and finally, we pick and process. Here's a closer look at each step:

  • Grouping Orders: The initial stage entails categorizing orders based on specific criteria. This can include product type, destination, order size, Service Level Agreements (SLA), cut-off times, and other pertinent factors. Grouping ensures that orders with similar attributes are picked in tandem, reducing the movements of pickers and boosting efficiency.
  • Releasing the Wave: Upon grouping the orders, they are prepared for the picking process. The release can be manually orchestrated based on a warehouse supervisor's discretion or be automated through warehouse management software. The timing and volume of this release are pivotal. A high batch factor (i.e. a higher number of orders processed together), especially in multi-order picking scenarios, leads to better utilization during picking. However, care must be taken to avoid overwhelming the system with excessive orders at once or causing bottlenecks in the picking lanes.
  • Picking and Processing: When a wave is released, pickers in the warehouse gather items for the batch, crucial for overall efficiency. Traditionally, collected items underwent sorting for individual orders, but advancements introduced innovative methods. Warehouses now use versatile strategies like multi-order picking and diverse workstations, optimizing resource utilization. This dynamic approach allows pickers to efficiently fulfill multiple customer orders simultaneously, using specialized picking carts. Technology integration with RF devices, pick-by-light, and voice-directed picking enhances accuracy and speed. Workstation configurations at the Autostore port reflect diversity, adapting to varying sorting strategies.

The role of technology: Guiding the wave

Modern wave picking is heavily reliant on technology. Warehouse management systems (WMS) play a crucial role in efficiently grouping orders, deciding on the optimal size of each wave, and ensuring that pickers have all the information they need at their fingertips. With advancements in AI and real-time data analytics, WMS can even predict order influx patterns, helping warehouses prepare and release waves in advance.

At its core, wave picking is about optimizing the workflow within a warehouse. By discerning the characteristics of incoming orders and aligning the picking process to address them in structured batches, warehouses can considerably enhance their throughput. This method not only reduces the movements of pickers but also maximizes the efficiency of Automated Storage and Retrieval Systems (ASRS). Through effective batching, a performance improvement of up to 30% can be swiftly achieved. It's a dynamic strategy that, when adeptly executed, ensures that warehouse operations flow as fluidly and robustly as waves on the ocean.

The core benefits and limitations of wave picking

In the realm of warehousing operations, achieving equilibrium is paramount for ensuring prime results. Wave picking encapsulates this equilibrium, mirroring the rhythmic undulations of the sea. We'll explore its diverse benefits and the potential hurdles that may accompany them.

  • Time efficiency: One of wave picking's primary advantages lies in the considerable time savings it offers. By releasing orders in waves, the picking process becomes more streamlined, allowing teams to efficiently handle their tasks and guarantee punctual order fulfillment.
  • Reducing congestion: Wave picking is instrumental in averting excessive crowding and congestion within warehouse aisles. Through coordinating the release of picking orders throughout different warehouse zones, it facilitates a smooth operational flow, diminishing the chances of traffic snarls.
  • Resource optimization: The tactical release of orders syncs with the resources at hand, ensuring that both the workforce and equipment are employed to their utmost potential. This results in minimized downtime and a superior utilization of existing assets.
  • System design and capital efficiency: Batching, a key component of wave picking, paves the way for more compactly designed systems. This not only aids in minimizing capital investments in highly efficient setups but also grants the WMS enhanced opportunities for batching. In a multi-order pick scenario, more targets can be catered to from a singular source.

However, every strategy has its set of challenges.

  • Flexibility Concerns: Though wave picking streamlines operations, it can occasionally display inflexibility. This rigidity can hinder swift adjustments to emergent or last-minute orders, a challenge especially significant in fluid sectors like e-commerce.
  • Dependency on Legacy Systems: While newer Warehouse Management Systems (WMS) are evolving to be more flexible with dynamic scheduling capabilities, wave picking has historically depended on legacy WMS systems. Such systems may not adapt as swiftly as their modern counterparts, potentially causing hiccups in ever-evolving market landscapes.
  • Labor Management Challenges: Orders' release, often determined by manual insights or historical data, can lead to disparities between the available workforce and the volume of orders. The optimal approach would be to let real-time data and analytics steer these decisions, but not every WMS has incorporated this feature yet.

In summation, while wave picking offers numerous advantages, it's essential to recognize its constraints. The key lies in capitalizing on its strengths and staying vigilant of its limitations, ensuring a harmonious and productive warehousing endeavor.

Tidal techniques: A deep dive into wave picking strategies

Warehousing strategies, much like the vast expanse of the ocean, have their unique currents and tides. In the realm of wave picking, there are distinct techniques, each with its rhythm and purpose. Let's have a look at the most prominent ones: Scheduled Waves, On-demand Waves, and Hybrid Approaches.

1. Scheduled Waves: Clockwork Precision

Scheduled waves are all about timing. In this approach, orders are released at predefined intervals, usually based on the warehouse's operational hours or specific shipment times. This method offers:

  • Predictability: By sticking to a set schedule, warehouses can better forecast their workforce and resource needs.
  • Batch Efficiency: Grouping orders into specific waves can maximize resource use, especially when dealing with similar or related orders.
  • Limitation: Its structured nature might mean it's less adaptable to unexpected changes or urgent order influxes.

2. On-demand Waves: Adaptive Order Management

On-demand wave picking adapts to the immediate flow of orders, offering a responsive strategy that is not industry-specific but rather centered around the order's nature and urgency. This method allows operations to release orders as they come in, prioritizing the need for speed and flexibility. It's a shift from industry-focused descriptions to a broader, situation-based perspective, emphasizing the system's capacity to address orders as they arise, without waiting for a wave to complete.

In practice, on-demand waves use real-time data to inform warehouse operations, preparing for the varying intensities of order traffic. Whether addressing a sudden surge in consumer electronics purchases, accommodating a quick turnover in fashion and apparel, or managing time-sensitive pharmaceutical deliveries, the focus is on configuring the WMS to respond to fluctuating order situations with agility.

Key aspects of this approach include:

  • Flexibility in processing orders irrespective of sector specifics, adjusting to the pace and scale of demand efficiently
  • Customer-oriented service, with a seamless fit for scenarios where quick dispatch is critical
  • A challenge in maintaining a real-time, responsive system that can pivot as needed, highlighting the importance of a dynamic WMS capable of such immediacy

This strategy calls for a nuanced understanding of order structures and a departure from traditional, industry-centric models, aiming to serve the fundamental requirement of timely and accurate order fulfillment.

Characteristics of On-demand Waves include:

  • Flexibility: As orders are released based on immediate demand, it's agile and can cater to unexpected market demands or urgent orders.
  • Customer-Centric: The method is particularly beneficial for sectors where customer demands can be erratic and time-sensitive.
  • Challenge: Requires a robust and real-time data management system to function effectively, as the focus is on instantaneous response.

3. Hybrid approaches: The best of both worlds

Hybrid approaches blend the scheduled and on-demand strategies. It might involve releasing a majority of orders on a set schedule while keeping a window open for on-demand needs. This ensures:

  • Adaptability: While the core operations run on a predictable schedule, there’s room to accommodate outliers or urgent requirements. AutoStore enables effortless scalability by adding more robots to the grid. This sets Autostore apart from competitors, providing a seamless solution to meet evolving operational needs.
  • Optimal Resource Utilization: Resources are primarily allocated based on the schedule, but with flexibility built in to handle real-time demands.
  • Complexity: This method requires a more sophisticated management system to ensure both strategies' smooth integration.

Each wave-picking strategy has its strengths, and the choice largely depends on the specific needs and nature of a business. Scheduled waves bring predictability, on-demand waves offer adaptability, and hybrid approaches attempt to capture the best of both. By understanding the unique demands of their operations and the expectations of their customer base, warehouses can select or customize a wave picking strategy that optimizes efficiency, responsiveness, and overall throughput.

The AutoStore preparation wave

The AutoStore bin preparation wave is a pivotal operation strategically designed to elevate the efficiency of the wave picking system. Contrary to the misconception that extensive bin relocation occurs during the night shift, our 24/7 operations strength emphasizes a swift preparation process, requiring a maximum of 30 minutes.

In this preparatory phase, bins are strategically repositioned during quieter periods to ensure optimal accessibility for upcoming orders. Crucially, this process doesn't entail a massive night shift relocation effort. Instead, it leverages advanced planning by our system design engineers. Key aspects of this planning include predicting the amount of urgent orders, bin distribution, and other parameters that influence the system's efficiency.  

Depending on the shift model and operator breaks, strategic use of this time can further optimize the system. Operators can utilize breaks to dig, impacting the number of robots needed and their charging times. Therefore, while night shifts contribute to general bin relocation, it's essential not to misconstrue the process as labor-intensive. Instead, it aligns with our commitment to efficient warehouse management through strategic planning and utilization of available time windows.

Read more: How the AutoStore system works

Transitioning from traditional picking to wave picking

The journey from traditional picking to wave picking can be perceived as formidable. Yet, with a methodical plan, this transition can yield substantial efficiency gains for businesses. Here's a structured guide to steer this transition:

  • Assess the Feasibility: The first step is to analyze your data to determine whether your product offering can be batched and waved. It's essential to discern if transitioning to wave picking aligns with your operational needs. For instance, a business with a product distribution of 65/35 or 60/40 might not find wave picking feasible, whereas a 90/10 or 95/5 distribution can significantly benefit.
  • Conduct a Comprehensive Analysis: With the feasibility established, delve into understanding the existing picking process. Identify the challenges, gauge the efficiency, and pinpoint areas ripe for enhancement. This exercise lays the foundation for a smooth transition.
  • Educate and Train the Workforce: The introduction of wave picking can represent a significant shift for warehouse teams. Organize training modules elucidating the new modus operandi, its merits, and the rationale behind this strategic pivot. Ensure that the team is conversant with the associated technology and tools.
  • Select the Appropriate Technology: Onboard a Warehouse Management System (WMS) compatible with wave picking. Depending on operational scale and budgetary considerations, this could vary from a rudimentary software suite to sophisticated systems augmented with AI and real-time analytical capabilities.
  • Pilot Test: Before a comprehensive rollout, orchestrate a pilot phase. Designate a segment of your warehouse or a specific order batch to induct wave picking. This preliminary phase will spotlight potential hurdles and pave the way for procedural refinement.
  • Phase-wise Deployment: Instead of overhauling the entire operational process in one go, strategize the transition in increments. This modulated approach minimizes operational disruptions and offers leeway to troubleshoot unforeseen challenges.
  • Engage in Continuous Review and Refinement: Post the wave picking induction, it's pivotal to institute periodic reviews. Scrutinize performance indicators, solicit staff feedback, and perpetually scout for optimization avenues.
  • Stay Abreast of Trends: Warehousing is an evolving domain. Dedicate resources to stay updated with cutting-edge wave picking technologies and methodologies to ensure sustained operational prowess.

A dedicated adherence to this roadmap, complemented by seamless communication channels, can empower businesses to transition from traditional picking paradigms to wave picking, crafting a future-proof warehousing ecosystem.

The future of warehousing: Wave-based centralization

The technological trajectory is set to redefine the contours of wave picking. While traditional WMS systems offer static solutions, the next phase in warehousing is pivoting towards real-time, data-driven frameworks. Such systems will be adept at instantaneous order processing, mirroring the mercurial market dynamics.

As centralization becomes more prominent and performance demands amplify, the solution won't always be direct amplification of system power or augmenting the number of pickers. Instead, the efficacy of wave and batch picking strategies can absorb and cater to these enhanced demands. Centralization, backed by such strategies, stands to be a major impetus for the warehousing evolution, driven in part by advanced AI and analytics that fine-tune processes.

How AutoStore supports wave picking

AutoStore is an automated storage and retrieval system that uses a Grid system where Robots transport inventory Bins to integrated Ports (workstations) for picking and replenishments. When it comes to wave picking, AutoStore can support this process in various ways:

1. Increased Efficiency: AutoStore Robots retrieve inventory Bins and bring them to the workstation, allowing workers to pick for multiple orders simultaneously. This minimizes the walking or travel time that traditional wave picking requires.

2. Seamless Integration with WMS: AutoStore can be integrated with Warehouse Management Systems (WMS) that handle wave picking strategies. This ensures that the right items are picked in the optimal sequence for each wave.

3. Batch Picking: While wave picking focuses on multiple orders in a 'wave,' batch picking (a component of wave picking) is about picking multiple orders in one go. AutoStore's system can facilitate batch picking by delivering Bins that cater to several orders, allowing the worker at the port station to pick for multiple orders from a single Bin or a sequence of Bins.

4. Dynamic Reorganization: AutoStore's system is inherently dynamic. The Robots can reposition Bins based on demand patterns. This means items that are frequently picked together in waves can be positioned in a manner that optimizes their retrieval.

5. Reduced Errors: With an automated system like AutoStore, the chances of picking errors are reduced. This ensures that wave picking is not only faster but also more accurate.

6. Flexibility in Wave Releases: Given the speed and efficiency of AutoStore robots, waves can be released more frequently, and in varying sizes, to meet demand peaks without overwhelming the picking stations.

In summary, while AutoStore doesn't inherently dictate a wave picking strategy, its features and functionalities can seamlessly support and enhance wave picking processes when integrated with the appropriate WMS or order management strategies.

AutoStore can support the process of wave picking in various ways.

Conclusion

As the warehousing world undergoes this transformative phase, we forecast that those warehouses that harness the potency of wave and batch picking - especially within centralized systems - will set the benchmark. They will be at the vanguard, dictating the paradigms of efficiency, performance, and customer satisfaction.

FAQ

What is the wave picking method?

Wave picking is a warehousing strategy where orders are grouped and released in batches or "waves" for streamlined picking and processing, optimizing efficiency and organization.

What is the difference between wave picking and batch picking?

Wave picking releases orders in grouped order waves based on various criteria like order type or destination, whereas batch picking involves grouping multiple orders to pick a particular product in bulk quantities before moving on to the next product.

What are the advantages of wave picking?

Advantages of wave picking include significant time savings, reduced congestion in warehouse aisles, optimal resource utilization, streamlined workflows, and enhanced order fulfillment efficiency. By using batch factors to reduce bin presentations at the port, wave picking also leads to less traffic on the AutoStore grid, ensuring that the same bins don't need to be retrieved multiple times. This process further contributes to the efficiency and speed of the warehouse operations.

How do you use a wave pick?

Using a wave pick involves three main steps: Grouping orders based on specified criteria, such as delivery schedules or destination zones, 2) Releasing the grouped orders for picking. This release can be handled manually by a supervisor at the respective dialog or automated within a Warehouse Management System (WMS), with some warehouses employing both methods to handle different areas, and 3) Picking and processing items for the entire batch, which are then sorted and packed for individual orders. The flexibility of a WMS in order release methods enhances the adaptability and efficiency of the wave picking process, aided by advanced technology to streamline warehouse operations.

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