diff --git a/core/c_seam.c b/core/c_seam.c
index 897de47..4d98d6d 100644
--- a/core/c_seam.c
+++ b/core/c_seam.c
@@ -12,67 +12,60 @@
 EXPORT int find_sharpest_seam_c(const double* pts, int M, int stride, double scale) {
     if (M < 3) return 0;
 
-    int64_t x_buf[1024];
-    int64_t y_buf[1024];
-    int64_t* x = (M <= 1024) ? x_buf : (int64_t*)malloc(M * sizeof(int64_t));
-    int64_t* y = (M <= 1024) ? y_buf : (int64_t*)malloc(M * sizeof(int64_t));
-
-    for (int i = 0; i < M; ++i) {
-        x[i] = (int64_t)llround(pts[i * stride + 0] * scale);
-        y[i] = (int64_t)llround(pts[i * stride + 1] * scale);
-    }
-
-    int64_t signed_area = (x[M - 1] * y[0] - x[0] * y[M - 1]);
-    for (int i = 0; i < M - 1; ++i) {
-        signed_area += (x[i] * y[i + 1] - x[i + 1] * y[i]);
-    }
-
-    if (signed_area == 0) {
-        if (M > 1024) { free(x); free(y); }
-        return 0;
+    // Find Y bounding range
+    double min_y = pts[1];
+    double max_y = pts[1];
+    for (int i = 1; i < M; ++i) {
+        double y = pts[i * stride + 1];
+        if (y < min_y) min_y = y;
+        if (y > max_y) max_y = y;
     }
+    double y_range = max_y - min_y;
+    double corner_bonus = (y_range > 0.0) ? (0.1 * y_range < 2.0 ? 0.1 * y_range : 2.0) : 2.0;
 
     int best_idx = 0;
-    double min_cos_concave = 2.0;
-    int best_concave_idx = -1;
-    double min_cos_overall = 2.0;
+    double best_score = -1e30;
+    double best_x = 1e30;
 
     for (int i = 0; i < M; ++i) {
         int prev = (i == 0) ? M - 1 : i - 1;
         int next = (i == M - 1) ? 0 : i + 1;
 
-        int64_t vin_x = x[i] - x[prev];
-        int64_t vin_y = y[i] - y[prev];
-        int64_t vout_x = x[next] - x[i];
-        int64_t vout_y = y[next] - y[i];
+        double xi = pts[i * stride + 0];
+        double yi = pts[i * stride + 1];
 
-        int64_t l2_in = vin_x * vin_x + vin_y * vin_y;
-        int64_t l2_out = vout_x * vout_x + vout_y * vout_y;
+        double vin_x = xi - pts[prev * stride + 0];
+        double vin_y = yi - pts[prev * stride + 1];
+        double vout_x = pts[next * stride + 0] - xi;
+        double vout_y = pts[next * stride + 1] - yi;
 
-        if (l2_in == 0 || l2_out == 0) continue;
+        double l_in = sqrt(vin_x * vin_x + vin_y * vin_y);
+        double l_out = sqrt(vout_x * vout_x + vout_y * vout_y);
 
-        int64_t cross = vin_x * vout_y - vin_y * vout_x;
-        int is_concave = (signed_area > 0) ? (cross < 0) : (cross > 0);
-
-        double dot = (double)(vin_x * vout_x + vin_y * vout_y);
-        double denom = sqrt((double)l2_in * (double)l2_out);
-        double cos_ang = dot / denom;
-
-        if (is_concave) {
-            if (cos_ang < min_cos_concave) {
-                min_cos_concave = cos_ang;
-                best_concave_idx = i;
-            }
+        double sharpness = 0.0;
+        if (l_in > 1e-7 && l_out > 1e-7) {
+            double dot = vin_x * vout_x + vin_y * vout_y;
+            double cos_ang = dot / (l_in * l_out);
+            if (cos_ang > 1.0) cos_ang = 1.0;
+            if (cos_ang < -1.0) cos_ang = -1.0;
+            sharpness = 1.0 - cos_ang; // 0 for straight line, 1 for 90 deg corner, 2 for 180 deg turnaround
         }
-        if (cos_ang < min_cos_overall) {
-            min_cos_overall = cos_ang;
+
+        double score = yi + sharpness * corner_bonus;
+
+        // Highest score wins (back of the object). Tie-break: smallest X for deterministic consistency across layers
+        if (score > best_score + 1e-6) {
+            best_score = score;
+            best_x = xi;
             best_idx = i;
+        } else if (fabs(score - best_score) <= 1e-6) {
+            if (xi < best_x) {
+                best_x = xi;
+                best_idx = i;
+            }
         }
     }
 
-    if (M > 1024) { free(x); free(y); }
-
-    if (best_concave_idx >= 0) return best_concave_idx;
     return best_idx;
 }
 
diff --git a/core/slice.py b/core/slice.py
index ecefb7b..cc0af37 100644
--- a/core/slice.py
+++ b/core/slice.py
@@ -190,89 +190,68 @@ def weld_vertices(tris: np.ndarray) -> tuple[np.ndarray, np.ndarray]:
     return unique_verts, faces
 
 
-def align_path_seam_sharpest(path: np.ndarray) -> np.ndarray:
+def find_path_seam(path: np.ndarray) -> int:
     """
-    Reorders a closed 2D/3D polygon path (N, 3) or (N, 2) so that its starting vertex (seam)
-    is located at the sharpest concave angle (inner corner). If no concave angles exist,
-    falls back to the sharpest angle overall.
-    
-    If path is open or has fewer than 3 distinct vertices, returns path unchanged.
-    Uses exact 1-micron integer arithmetic for orientation and angle selection.
+    Finds the optimal starting vertex index (seam) positioned at the back of the object (+Y).
+    Uses a weighted heuristic prioritizing maximum Y with a sharpness bonus for corners,
+    with deterministic tie-breaking for consistent vertical layer alignment.
     """
-    if len(path) < 4:
-        return path
-
-    if not is_closed_path(path):
-        return path
+    if len(path) < 4 or not is_closed_path(path):
+        return 0
 
     pts = path[:-1]
     M = len(pts)
     if M < 3:
-        return path
+        return 0
 
     if _c_seam_lib is not None:
         try:
             c_pts = np.ascontiguousarray(pts, dtype=np.float64)
             stride = int(c_pts.shape[1])
             ptr = c_pts.ctypes.data_as(ctypes.POINTER(ctypes.c_double))
-            best_idx = int(_c_seam_lib.find_sharpest_seam_c(ptr, M, stride, float(SCALE)))
-            if best_idx == 0:
-                return path
-            res = np.empty_like(path)
-            split = M - best_idx
-            res[:split] = path[best_idx:-1]
-            res[split:] = path[:best_idx + 1]
-            return res
+            return int(_c_seam_lib.find_sharpest_seam_c(ptr, M, stride, float(SCALE)))
         except Exception:
             pass
 
-    pts_um = np.rint(pts[:, :2] * SCALE).astype(np.int64)
-    x = pts_um[:, 0]
-    y = pts_um[:, 1]
-    signed_area_um = np.sum(x[:-1] * y[1:] - x[1:] * y[:-1]) + (x[-1] * y[0] - x[0] * y[-1])
-    if signed_area_um == 0:
+    # NumPy fallback
+    x = pts[:, 0]
+    y = pts[:, 1]
+    y_min, y_max = float(np.min(y)), float(np.max(y))
+    y_range = y_max - y_min
+    bonus = min(2.0, 0.1 * y_range) if y_range > 0 else 2.0
+
+    prev_pts = np.roll(pts[:, :2], 1, axis=0)
+    next_pts = np.roll(pts[:, :2], -1, axis=0)
+
+    v_in = pts[:, :2] - prev_pts
+    v_out = next_pts - pts[:, :2]
+
+    l_in = np.linalg.norm(v_in, axis=1)
+    l_out = np.linalg.norm(v_out, axis=1)
+
+    valid = (l_in > 1e-7) & (l_out > 1e-7)
+    cos_ang = np.ones(M, dtype=np.float64)
+    cos_ang[valid] = np.sum(v_in[valid] * v_out[valid], axis=1) / (l_in[valid] * l_out[valid])
+    cos_ang = np.clip(cos_ang, -1.0, 1.0)
+    sharpness = 1.0 - cos_ang
+
+    scores = y + sharpness * bonus
+    # Deterministic tie-break: highest score, smallest x
+    return int(np.lexsort((x, -scores))[0])
+
+
+def align_path_seam_sharpest(path: np.ndarray) -> np.ndarray:
+    """
+    Reorders a closed 2D/3D polygon path (N, 3) or (N, 2) so that its starting vertex (seam)
+    is located at the back of the object (highest Y with corner preference).
+    
+    If path is open or has fewer than 3 distinct vertices, returns path unchanged.
+    """
+    if len(path) < 4 or not is_closed_path(path):
         return path
 
-    v_in = np.empty((M, 2), dtype=np.int64)
-    v_in[0, 0] = x[0] - x[-1]
-    v_in[0, 1] = y[0] - y[-1]
-    v_in[1:, 0] = x[1:] - x[:-1]
-    v_in[1:, 1] = y[1:] - y[:-1]
-
-    l2_in = v_in[:, 0]**2 + v_in[:, 1]**2
-    valid_in = l2_in > 0
-    valid_out = np.empty_like(valid_in)
-    valid_out[:-1] = valid_in[1:]
-    valid_out[-1] = valid_in[0]
-    valid = valid_in & valid_out
-    if not np.any(valid):
-        return path
-
-    cross_2d = np.empty(M, dtype=np.int64)
-    cross_2d[:-1] = v_in[:-1, 0] * v_in[1:, 1] - v_in[:-1, 1] * v_in[1:, 0]
-    cross_2d[-1] = v_in[-1, 0] * v_in[0, 1] - v_in[-1, 1] * v_in[0, 0]
-
-    concave_mask = valid & (cross_2d < 0) if signed_area_um > 0 else valid & (cross_2d > 0)
-
-    l_in = np.sqrt(l2_in, dtype=np.float64)
-    l_out = np.empty_like(l_in)
-    l_out[:-1] = l_in[1:]
-    l_out[-1] = l_in[0]
-
-    dot_prods = np.empty(M, dtype=np.float64)
-    dot_prods[:-1] = v_in[:-1, 0] * v_in[1:, 0] + v_in[:-1, 1] * v_in[1:, 1]
-    dot_prods[-1] = v_in[-1, 0] * v_in[0, 0] + v_in[-1, 1] * v_in[0, 1]
-
-    cos_angles = np.full(M, 1.0)
-    denom = l_in[valid] * l_out[valid]
-    cos_angles[valid] = dot_prods[valid] / denom
-
-    if np.any(concave_mask):
-        concave_indices = np.where(concave_mask)[0]
-        best_idx = int(concave_indices[np.argmin(cos_angles[concave_mask])])
-    else:
-        best_idx = int(np.argmin(cos_angles))
-
+    M = len(path) - 1
+    best_idx = find_path_seam(path)
     if best_idx == 0:
         return path
 
@@ -283,6 +262,7 @@ def align_path_seam_sharpest(path: np.ndarray) -> np.ndarray:
     return res
 
 
+
 class SlicePaths(list[np.ndarray]):
     groups: list[int]
     extrusion_rate: list[np.ndarray]
@@ -681,11 +661,10 @@ class SlicePaths(list[np.ndarray]):
 
     def align_seams(self, mode: str = "sharpest") -> SlicePaths:
         """
-        Aligns the seams (starting point of closed paths) in SlicePaths.
-        Supported modes: 'sharpest'.
-        Uses 1-micron integer math.
+        Aligns the seams (starting point of closed paths) in SlicePaths to the back (+Y).
+        Preserves all per-path and per-vertex attributes.
         """
-        if not self or mode != "sharpest":
+        if not self:
             return self
 
         new_paths: list[np.ndarray] = []
@@ -702,9 +681,9 @@ class SlicePaths(list[np.ndarray]):
                     new_extra[k].append(self.extra_attributes[k][i])
                 continue
 
-            pts = p[:-1]
-            M = len(pts)
-            if M < 3:
+            M = len(p) - 1
+            best_idx = find_path_seam(p)
+            if best_idx == 0:
                 new_paths.append(p)
                 new_ext.append(self.extrusion_rate[i])
                 new_feed.append(self.feedrate[i])
@@ -712,60 +691,6 @@ class SlicePaths(list[np.ndarray]):
                     new_extra[k].append(self.extra_attributes[k][i])
                 continue
 
-            if _c_seam_lib is not None:
-                try:
-                    c_pts = np.ascontiguousarray(pts, dtype=np.float64)
-                    stride = int(c_pts.shape[1])
-                    ptr = c_pts.ctypes.data_as(ctypes.POINTER(ctypes.c_double))
-                    best_idx = int(_c_seam_lib.find_sharpest_seam_c(ptr, M, stride, float(SCALE)))
-                except Exception:
-                    best_idx = 0
-            else:
-                pts_um = np.round(pts[:, :2] * SCALE).astype(np.int64)
-                x = pts_um[:, 0]
-                y = pts_um[:, 1]
-                x_next = np.roll(x, -1)
-                y_next = np.roll(y, -1)
-                signed_area_um = np.sum(x * y_next - x_next * y)
-
-                prev_pts = np.roll(pts_um, 1, axis=0)
-                next_pts = np.roll(pts_um, -1, axis=0)
-
-                v_in = pts_um - prev_pts
-                v_out = next_pts - pts_um
-
-                l2_in = np.sum(v_in**2, axis=1)
-                l2_out = np.sum(v_out**2, axis=1)
-
-                valid = (l2_in > 0) & (l2_out > 0)
-                if not np.any(valid) or signed_area_um == 0:
-                    best_idx = 0
-                else:
-                    cross_2d = v_in[:, 0] * v_out[:, 1] - v_in[:, 1] * v_out[:, 0]
-                    if signed_area_um > 0:
-                        concave_mask = valid & (cross_2d < 0)
-                    else:
-                        concave_mask = valid & (cross_2d > 0)
-
-                    l_in = np.sqrt(l2_in.astype(np.float64))
-                    l_out = np.sqrt(l2_out.astype(np.float64))
-
-                    cos_angles = np.full(M, 1.0)
-                    dot_prods = np.sum(v_in[valid] * v_out[valid], axis=1).astype(np.float64)
-                    cos_angles[valid] = dot_prods / (l_in[valid] * l_out[valid])
-
-                    if np.any(concave_mask):
-                        concave_indices = np.where(concave_mask)[0]
-                        best_idx = int(concave_indices[np.argmin(cos_angles[concave_mask])])
-                    else:
-                        best_idx = int(np.argmin(cos_angles))
-
-            if best_idx == 0:
-                new_paths.append(p)
-                new_ext.append(self.extrusion_rate[i])
-                new_feed.append(self.feedrate[i])
-                for k in self.extra_attributes:
-                    new_extra[k].append(self.extra_attributes[k][i])
             else:
                 new_p = np.empty_like(p)
                 split = M - best_idx
diff --git a/doc/MODULES.md b/doc/MODULES.md
index d29e8df..35dc015 100644
--- a/doc/MODULES.md
+++ b/doc/MODULES.md
@@ -28,8 +28,8 @@ This file provides a mapping of modules to their primary responsibilities and ke
 - `slice.py`:
     - `slice_at_range()`: Top-level slicing function that iterates through Z-heights using `manifold3d` for guaranteed watertight solid slicing (resolving coplanar and floating-point degeneracies) with a fallback to `trimesh` multiplane slicing for open sheets (supports `ignore_holes` option).
     - `_slice_single_mesh()`: Mesh slicer implementing `manifold3d` solid slicing and `trimesh` multiplane intersection with micro-epsilon perturbation at boundary faces.
-    - `align_path_seam_sharpest()`: High-performance vectorized heuristic that positions the start vertex (seam) of closed polygon loops at the sharpest concave angle (inner corner), with fallback to sharpest angle overall.
-    - `SlicePaths.align_seams()`: Method on `SlicePaths` to align path seams to sharpest concave angles while preserving per-vertex attributes and metadata.
+    - `align_path_seam_sharpest()`: High-performance vectorized heuristic that positions the start vertex (seam) of closed polygon loops at the back of the object (+Y) with corner sharpness preference.
+    - `SlicePaths.align_seams()`: Method on `SlicePaths` to align path seams to the back (+Y) while preserving per-vertex attributes and metadata.
     - `Pather`: Class that converts toolpaths into G-code strings. Supports per-segment extrusion rates, feedrates, and custom extra attributes.
     - `segments_to_slice()`: Utility to convert raw intersection segments into continuous paths (closed polygons are processed via Pyclipper, supports `ignore_holes`, open paths remain open).
     - `link_segments()`: Logic for joining loose segments into continuous paths.
diff --git a/doc/NODES.md b/doc/NODES.md
index 951f18f..5c0c97f 100644
--- a/doc/NODES.md
+++ b/doc/NODES.md
@@ -80,7 +80,7 @@ All nodes are found in the **Add (Shift+A)** menu under the **SliceNodes** categ
     - **Extrusion Multiplier Attribute**: Mesh attribute to use for per-segment extrusion rates.
     - **Feedrate Attribute**: Mesh attribute to use for per-segment feedrates.
     - **Extra Attributes**: Dictionary mapping mesh attribute names to custom G-code prefixes (e.g., `opening_size` -> `S`).
-- **Slice Shells**: Slices a `SlicingObject` into 2D `SlicePaths` at a given layer height. Automatically aligns path seams to the sharpest concave angle (inner corner) of each layer. Supports rotation for slicing at an angle.
+- **Slice Shells**: Slices a `SlicingObject` into 2D `SlicePaths` at a given layer height. Automatically aligns path seams to the back (+Y) of each layer. Supports rotation for slicing at an angle.
     - **Ignore Holes**: Boolean option to omit interior hole perimeters and generate only the outer shell boundaries.
 - **Buffer Shells**: Offsets/buffers 2D `SlicePaths`. Supports rotated offsetting and multiple miter types.
 - **Buffer Shells Multiple**: Offsets 2D `SlicePaths` with multiple buffer passes.
diff --git a/tests/test_slice.py b/tests/test_slice.py
index 9f7924e..8cf1b94 100644
--- a/tests/test_slice.py
+++ b/tests/test_slice.py
@@ -725,9 +725,7 @@ class TestSlice(unittest.TestCase):
 
     def test_align_seam_sharpest_triangle(self):
         from NodeSlicer.core.slice import align_path_seam_sharpest
-        # Right triangle with acute 30-degree vertex at (10, 0)
-        # Vertices: 90 deg at (0,0), 60 deg at (0, 5.7735), 30 deg at (10,0)
-        # Start at 90 deg vertex (0,0)
+        # Right triangle with acute vertex at (10,0) and back vertex at (0, 5.7735)
         path = np.array([
             [0.0, 0.0, 0.0],
             [0.0, 5.7735, 0.0],
@@ -736,8 +734,8 @@ class TestSlice(unittest.TestCase):
         ])
         aligned = align_path_seam_sharpest(path)
         self.assertTrue(np.allclose(aligned[0], aligned[-1]))
-        # Sharpest angle is 30 degrees at (10.0, 0.0)
-        np.testing.assert_allclose(aligned[0, :2], [10.0, 0.0], atol=1e-3)
+        # Back seam should be placed at the rear-most vertex (+Y) at (0.0, 5.7735)
+        np.testing.assert_allclose(aligned[0, :2], [0.0, 5.7735], atol=1e-3)
 
     def test_slicepaths_align_seams(self):
         from NodeSlicer.core.slice import SlicePaths
@@ -777,8 +775,9 @@ class TestSlice(unittest.TestCase):
         aligned = align_path_seam_sharpest(path)
         self.assertEqual(len(aligned), len(path))
         self.assertTrue(np.allclose(aligned[0], aligned[-1]))
-        # Seam should be placed at the concave inner corner (5.0, 5.0)
-        np.testing.assert_allclose(aligned[0, :2], [5.0, 5.0])
+        # Back seam should be placed on the rear corner (+Y) at (0.0, 10.0)
+        np.testing.assert_allclose(aligned[0, :2], [0.0, 10.0])
+
 
     def test_intrinsics_retraction_feedrate(self):
         from NodeSlicer.core.nodeslicer.nodes.base import SliceIntrinsics
diff --git a/tests/visual/images/01_max_coverage_overlapping_squares.png b/tests/visual/images/01_max_coverage_overlapping_squares.png
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diff --git a/tests/visual/images/02_max_coverage_donut_and_box.png b/tests/visual/images/02_max_coverage_donut_and_box.png
index 121cc9b..7e3c22f 100644
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diff --git a/tests/visual/images/03_min_coverage_staggered_layers.png b/tests/visual/images/03_min_coverage_staggered_layers.png
index bc0e4fd..46a3cff 100644
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diff --git a/tests/visual/images/04_min_coverage_overlapping_squares.png b/tests/visual/images/04_min_coverage_overlapping_squares.png
index e32cfdd..96250f6 100644
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diff --git a/tests/visual/images/06_intersection_staggered_layers.png b/tests/visual/images/06_intersection_staggered_layers.png
index 540d7ef..3272621 100644
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diff --git a/tests/visual/images/07_subtract_hole_creation.png b/tests/visual/images/07_subtract_hole_creation.png
index 37a8b54..94196e5 100644
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diff --git a/tests/visual/images/08_xor_overlapping_squares.png b/tests/visual/images/08_xor_overlapping_squares.png
index ddb8304..f2f8cd6 100644
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diff --git a/tests/visual/images/11_max_coverage_concentric_perimeters.png b/tests/visual/images/11_max_coverage_concentric_perimeters.png
index a17f5bd..e2b8bf5 100644
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diff --git a/tests/visual/images/12_min_coverage_concentric_perimeters.png b/tests/visual/images/12_min_coverage_concentric_perimeters.png
index 2778f12..4377adc 100644
Binary files a/tests/visual/images/12_min_coverage_concentric_perimeters.png and b/tests/visual/images/12_min_coverage_concentric_perimeters.png differ
diff --git a/tests/visual/images/13_max_coverage_single_input_perimeters.png b/tests/visual/images/13_max_coverage_single_input_perimeters.png
index 572d1aa..45fccb8 100644
Binary files a/tests/visual/images/13_max_coverage_single_input_perimeters.png and b/tests/visual/images/13_max_coverage_single_input_perimeters.png differ
diff --git a/tests/visual/images/14_min_coverage_single_input_perimeters.png b/tests/visual/images/14_min_coverage_single_input_perimeters.png
index a155741..2933eba 100644
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